The present report introduces a new construction of sequences having both a low peak factor (crest factor) and a flat power spectrum. Since the proposed sequence has a flat power spectrum, its auto-correlation is zero except for the zero shift. The proposed construction uses a systematic scheme and no search method. The length of the proposed sequence is (2n+1)(4n+1) for an arbitrary integer n. The sequence construction presented herein provides a means for generating various sequences at the lengths required for such applications as system measurement (which requires uncorrelated test signals), and audio signal processing for sound production (for enhancing spatial imagery in stereo signals synthesized from mono sources).

This paper presents an algorithm to analyze the stability and detect an upper-bound of every possible overload of a ΣΔ modulator for a set of input signals that are characterized by specified peak amplitudes and auto-correlations. The approach is to introduce a hyper cube in which all possible state vectors are recursively mapped into a subset of the hyper cube itself for the specified inputs and detect such a hyper cube by iteratively solving linear programming problems. Then the proposed algorithm may not identify every stable ΣΔ modulator but cannot evaluate any unstable ΣΔ modulator as a stable one. In numerical examples, two 1-bit ΣΔ modulators are analyzed, and it is revealed that a band-limitation of inputs to OSR 256 guarantees the rigorous stability even with an extension of input range to at least 240% of conventional range.

The Camera sensor network is a new advent of technology in which each sensor node can capture video signal, process and communicate with other nodes. We have investigated a dense node configuration. The requested processing task in this network is arbitrary view generation among nodes view. To avoid unnecessary communication between nodes in this network and to speed up the processing time, we propose a distributed processing architecture where the number of nodes sharing image data are optimized. Therefore, each sensor node processes part of the interpolation algorithm with local communication between sensor nodes. Two processing methods are used based on the image size shared. These two methods are F-DP (Fully image shared Distributed Processing) and P-DP (Partially image shared Distributed Processing). In this research, the network processing time has been theoretically analyzed for one user. The theoretical results are compatible with the experimental results. In addition, the performance of proposed DP methods were compared with Centralized Processing (CP). As a result, the best processing method for optimum number of nodes can be chosen based on (i) communication delay of the network, (ii) whether the network has one or more channels for communication among nodes and (iii) the processing ability of nodes.

In image-based relighting (IBR), users are allowed to control the illumination condition of a scene or an object. A relighting data set (RDS) contains a large number of reference images captured under various directional light sources. This paper proposes a principal component analysis (PCA) based compression scheme that effectively reduces the data volume. Since the size of images is very large, a tiling recursive least square PCA (RLS-PCA) is used. The output of RLS-PCA is a set of eigenimages and the corresponding eigen coefficients. To further compress the data, extracted eigenimages are compressed using transform coding while extracted eigen coefficients are compressed using uniform quantization with entropy coding. Our simulation shows that the proposed approach is superior to compressing reference images with JPEG and MPEG2.

A novel binary line-pattern algorithm for embedded fingerprint authentication system is introduced in this paper. In this algorithm, each line-pattern is a one-dimension binary matrix that describes the alternation pattern of ridge and valley in fingerprint image. Two parallel lines or two cross lines in a certain scope make up related line-pattern pair. Several such line-pattern pairs at different parts of a fingerprint image can describe another intrinsic feature besides traditional minutiae feature. Experimental results showed this algorithm was not only efficient but also effective. Furthermore, a hybrid fingerprint match scheme is also introduced in this paper. It has the following features: (i) minutiae matching is firstly carried out to calculate the similarity score between the query fingerprint and the template fingerprint, and moreover, the translation and rotation parameters are obtained at the same time; (ii) line-pattern algorithm is immediately performed based on the parameters obtained after minutiae matching to get another similarity score; (iii) the final matching score is the combination of the minutiae matching score and the line-pattern matching score. Experiments were conducted on the FVC2002 database and our private database respectively. Both of the results were inspiring. In detail, at the same FAR value, the FRR of this hybrid match algorithm is to be 2-8% lower than only minutiae-based matching algorithm.

A new and fast fingerprint classification method based on direction patterns is presented in this paper. This method is developed to be applicable to today's embedded fingerprint authentication system, in which small area sensors are widely used. Direction patterns are well treated in the direction map at block level, where each block consists of 88 pixels. It is demonstrated that the search of directions pattern in specific area, generally called as pattern area, is able to classify fingerprints clearly and quickly. With our algorithm, the classification accuracy of 89% is achieved over 4000 images in the NIST-4 database, slightly lower than the conventional approaches. However, the classification speed is improved tremendously up to about 10 times as fast as conventional singular point approaches.

Motion estimation is the key issue in video compressing. Several methods for motion estimation based on the center biased strategy and minimum mean square error trend searching have been proposed, such as TSS, FSS, UCBDS and MIBAS, but these methods yield poor estimates or find local minima. Many other methods predict the starting point for the estimation; such methods include PMEA, PSA and GPS: these can be fast but are inaccurate. This study addresses the causes of wrong estimates, local minima and incorrect predictions in the prior estimation methods. The Multiple Searching Trend (MST) is proposed to overcome the problems of ineffective searches and local minima, and the Adaptive Dilated Searching Field (ADSF) is described to prevent prediction from wrong location. Applying MST and ADSF to the listed estimating methods, such as UCBDS, a fast and accurate can be reached. For this this reason, the method is called CockTail Searching (CTS).

This paper proposes the tile size conversion method for the wavelet image transcoding gateway and a set of methods to reduce the tile boundary artifacts caused by the conversion. In the wavelet image coding system represented by JPEG 2000, pictures are usually divided into one or more tiles and each tile is then transformed separately. On low memory terminals such as mobile terminals, some decoders are likely to have limits on what tile sizes they can decode. Assuming a system using these limited decoders, methods were investigated for converting the tile size quickly and automatically at the gateway when image data with a non-decodable tile size is received at the gateway from another system. Furthermore, tile boundary artifacts reduction methods are investigated. This paper verifies the validity of the proposed scheme by implementing it with a (5, 3) reversible filter and a (9, 7) irreversible filter. In addition, we implemented the tile size conversion gateway and evaluated the performance of the processing time. The results show the validity of the conversion gateway.

This paper presents a technique for high-accuracy correspondence search between two images using Phase-Only Correlation (POC) and its performance evaluation in a 3D measurement application. The proposed technique employs (i) a coarse-to-fine strategy using image pyramids for correspondence search and (ii) a sub-pixel window alignment technique for finding a pair of corresponding points with sub-pixel displacement accuracy. Experimental evaluation shows that the proposed method makes possible to estimate the displacement between corresponding points with approximately 0.05-pixel accuracy when using 1111-pixel matching windows. This paper also describes an application of the proposed technique to passive 3D measurement system.

We propose a new algorithm for overdetermined blind source separation (BSS) based on multistage independent component analysis (MSICA). To improve the separation performance, we have proposed MSICA in which frequency-domain ICA and time-domain ICA are cascaded. In the original MSICA, the specific mixing model, where the number of microphones is equal to that of sources, was assumed. However, additional microphones are required to achieve an improved separation performance under reverberant environments. This leads to alternative problems, e.g., a complication of the permutation problem. In order to solve them, we propose a new extended MSICA using subarray processing, where the number of microphones and that of sources are set to be the same in every subarray. The experimental results obtained under the real environment reveal that the separation performance of the proposed MSICA is improved as the number of microphones is increased.

The conventional algorithms in the echo canceling system have drawback when they are faced with double-talk condition in noisy environment. Since the double-talk and noise signal are exist, then the error signal is contaminated to estimate the gradient correctly. In this paper, we define a new class of adaptive algorithm for tap adaptations, based on the correlation function processing. The computer simulation results show that the Correlation LMS (CLMS) and the Extended CLMS (ECLMS) algorithms have better performance than conventional LMS algorithm. In order to implement the ECLMS algorithm, the Frequency domain Extended CLMS (FECLMS) algorithm is proposed to reduce the computational complexity. However the convergence speed is not sufficient. In order to improve the convergence speed, the Wavelet domain Extended CLMS (WECLMS) algorithm is proposed. The computer simulation results support the theoretical findings and verify the robustness of the proposed WECLMS algorithm in the double-talk situation.

This paper describes a real-time blind source separation (BSS) method for moving speech signals in a room. Our method employs frequency domain independent component analysis (ICA) using a blockwise batch algorithm in the first stage, and the separated signals are refined by postprocessing using crosstalk component estimation and non-stationary spectral subtraction in the second stage. The blockwise batch algorithm achieves better performance than an online algorithm when sources are fixed, and the postprocessing compensates for performance degradation caused by source movement. Experimental results using speech signals recorded in a real room show that the proposed method realizes robust real-time separation for moving sources. Our method is implemented on a standard PC and works in realtime.

In this paper, we propose two adaptive filtering schemes for Stereophonic Acoustic Echo Cancellation (SAEC), which are based on the adaptive projected subgradient method (Yamada et al., 2003). To overcome the so-called non-uniqueness problem, the schemes utilize a certain preprocessing technique which generates two different states of input signals. The first one simultaneously uses, for fast convergence, data from two states of inputs, meanwhile the other selects, for stability, data based on a simple min-max criteria. In addition to the above difference, the proposed schemes commonly enjoy (i) robustness against noise by introducing the stochastic property sets, and (ii) only linear computational complexity, since it is free from solving systems of linear equations. Numerical examples demonstrate that the proposed schemes achieve, even in noisy situations, compared with the conventional technique, (i) much faster and more stable convergence in the learning process as well as (ii) lower level mis-identification of echo paths and higher level Echo Return Loss Enhancement (ERLE) around the steady state.

This paper proposes an alternative learning algorithm for a stereophonic acoustic echo canceller without pre-processing which can identify the correct echo-paths. By dividing the filter coefficients into the former/latter parts and updating them alternatively, conditions both for unique solution and for perfect echo cancellation are satisfied. The learning for each part is switched from one part to the other when that part converges. Convergence analysis clarifies the condition for correct echo-path identification. For fast and stable convergence, a convergence detection and an adaptive step-size are introduced. The modification amount of the filter coefficients determines the convergence state and the step-size. Computer simulations show 10 dB smaller filter coefficient error than those of the conventional algorithms without pre-processing.

This paper proposes a new implementation of an adaptive noise canceller based upon a parallel block structure, which aims to raise the processing and convergence rates and to improve the steady-state performance. The procedure is as follows: First, an IIR bandpass filter with a variable center angular frequency using adaptive Q-factor control and two adaptive control signal generators are realized by the parallel block structure. Secondly, a new algorithm for adaptive Q-factor control with parallel block structure is proposed to improve the convergence characteristic. In addition, the steady-state performance of the filter is stabilized by using the variable step size parameter in adaptive control of the center frequency and the speed up of the convergence rate is achieved by adopting a normalized gradient algorithm for adaptive control. Finally, simulation results are given to demonstrate the convergence performance.

This paper presents a novel blind multiple access interference (MAI) suppression filter in DS/CDMA systems. The filter is adaptively updated by parallel projections onto a series of convex sets. These sets are defined based on the received signal as well as a priori knowledge about the desired user's signature. In order to achieve fast convergence and good performance at steady state, the adaptive projected subgradient method (Yamada et al., 2003) is applied. The proposed scheme also jointly estimates the desired signal amplitude and the filter coefficients based on an approximation of an EM type algorithm, following the original idea proposed by Park and Doherty, 1997. Simulation results highlight the fast convergence behavior and good performance at steady state of the proposed scheme.

In uplink multicarrier code division multiple access (MC-CDMA), the inter-code interference (ICI) caused by the independent and frequency-selective fading channel of each user and the inter-carrier interference caused by the asynchronous reception of each user's OFDM symbols result in multiple access interference (MAI). This paper evaluates the ICI in frequency-selective Rayleigh fading channels for uplink MC-CDMA. We derive theoretical expressions for the desired-to-undesired signal power ratio (DUR) as a quantitative representation of ICI, and validate them by comparison with computer simulations using a Walsh-Hadamard (WH) code. Based on the analytical results, we obtain the optimum spreading sequence that minimizes the ICI (in short, maximizes the multiplexing performance); this sequence appears to be orthogonal. Three equalization combining methods are examined; equal gain combining (EGC), orthogonality restoring combining (ORC), and maximum ratio combining (MRC).

Decision-directed, pilot-symbol-aided channel estimation (PSACE) for coded orthogonal frequency division multiplexing (COFDM) systems has structurally unavoidable processing delay owing to the generation of new reference data. In a fast fading environment, the channel condition which varies during the delay induces channel estimation error. This paper proposes a method of reducing this estimation error. In this method, channel equalization is performed for the received signal twice. One is done as pre-equalization with the delayed estimates of channel frequency response in order to update them periodically. At the same moment, the other is done as post-equalization for the received signal that is delayed by the processing delay time, with the same estimates as the pre-equalization. By the proposed method, more accurate channel estimation can be realized without significant output delay. Computer simulations are performed by utilizing the IEEE 802.11a packet structure of 24 Mbit/s. The result shows that the proposed OFDM transmission scheme having the delay time of 20 µs offers 2.5 dB improvement in the required E_b/N₀ at PER = 10^-2 in the ESTI-BRAN model C Rayleigh fading channel with f_d = 500 Hz.

Under current radio regulations, it is illegal to change the configuration of a radio after its type approval has been acquired. However, the reconfigurability of a Software Defined Radio (SDR) terminal, which is one of its benefits, is possible by changing its software in the field. This contradicts current radio regulations. Therefore, a new authorization procedure is necessary for system reconfiguration using SDR. It is necessary to satisfy the radio regulation. In other words, a new authorization procedure requires techniques to prevent the operation out of the allowed limits of SDR in the field. In this paper, we propose a novel mechanism, called Automatic Certification System (ACS), as a solution to these regulatory issues for SDR. The ACS is a system which gives type approval automatically to the software which affects the output power, central frequency, frequency band, modulation type and which controls analog circuits on an SDR terminal. We also propose the ACS based framework which aims to distribute the burden of the software manufacturer, hardware manufacturer, and governmental authority. After that, we describe the inspection method and discuss the case of a modulation scheme which can be Phase Shift Keying (PSK) or Minimum Shift Keying (MSK) schemes. Our simulations confirm that the ACS is able to certify the modulation software at the terminal.

Classical designs of maximally flat finite impulse response digital filters need to perform inverse discrete Fourier transformation of the frequency responses, in order to calculate the impulse response coefficients. Several attempts have been made to simplify the designs by obtaining explicit formulas for the impulse response coefficients. Such formulas have been derived for digital differentiators having maximal linearity at zero frequency, using different techniques including interpolating polynomials and the Taylor series etc. We show that these formulas can be obtained directly by application of maximal linearity constraints on the frequency response. The design problem is formulated as a system of linear equations, which can be solved to achieve maximal linearity at an arbitrary frequency. Certain special characteristics of the determinant of the coefficients matrix of these equations are explored for designs centered at zero frequency, and are used in derivation of explicit formulas for the impulse response coefficients of digital differentiators of both odd and even lengths.

A new indirect approach for designing low-order linear-phase IIR filters is presented in this paper. Given an FIR filter, we utilize a new Krylov subspace projection method, called the rational Arnoldi method with adaptive orders, to synthesize an approximated IIR filter with small orders. The synthesized IIR filter can truly reflect essential dynamical features of the original FIR filter and indeed satisfies the design specifications. Also, from simulation results, it can be observed that the linear-phase property in the passband is stilled retained. This indirect approach is accomplished using the state-space realization of FIR filters, multi-point Pade approximations, the Arnoldi algorithm, and an intelligent scheme to select expansion points in the frequency domain. Such methods are quite efficient in terms of computational complexity. Fundamental developments of the proposed method will be discussed in details. Numerical results will demonstrate the accuracy and the efficiency of this two-step indirect method.

In this paper, we propose a design method of filters by successive projection (SP) method using multiple extreme frequency points based on Fritz John's theorem. In conventional SP method, only one extreme frequency point at which the deviation from the given specification is maximized is used in the update of the filter coefficients. Therefore, enormous amount of iteration numbers are necessary for research the solution which satisfies the given specification. In the proposed method, the updating coefficient using multiple extreme frequency points is possible by Fritz John's theorem. As a result, the solution converges less iteration number than the conventional SP method.

This paper provides a novel signal processing for detecting defects based on the spatio-temporal gradient analysis over the Lamb-wave field. The proposed processing classifies the wave field through the rank of the covariance matrix which is defined by the four-dimensional vector with following components: a vertical displacement, its vertical velocity, and a pair of out-of-plane shearing strains. The covariance matrix provides the information about defects. Its determinant, therefore, is proposed as the inhomogeneity-index of the object surface. In this study, the physical meanings of the proposed index are shown, the computational process in the Lamb-wave field near the defects is discussed and their behaviors are investigated through FDTD-simulations and acoustic experiments.

A novel public watermarking algorithm based on chaotic properties is proposed. Thanks to good randomness and easy reproducibility of chaos, firstly the watermark is permuted by chaotic sequences, then a small number of reference points are selected randomly in the middle frequency bands of DCT domain, and the variable number disorder watermark bits are embedded into the neighborhood of each reference point according to chaotic sequences. The experimental results show the invisibility and robustness.

Based on Radon transform, a novel method for registering a periodic (self-referencing) watermark is presented. Although the periodic watermark is widely used as a countermeasure for affine transformation, there is no known efficient method to register it. Experimental results show that the proposed method is effective for registering the watermark from an image that had undergone both affine transformations and severe lossy compression.

This paper proposes a learning classifier based on Support Vector Domain Description (SVDD) for two-class problem. First, by the description of the training samples from one class, a sphere boundary containing these samples is obtained; then, this boundary is used to classify the test samples. In addition, instead of the traditional quadratic programming, multiplicative updates is used to solve the Lagrange multiplier in optimizing the solution of the sphere boundary. The experiment on CBCL face database illustrates the effectiveness of this learning algorithm in comparison with Support Vector Machine (SVM) and Sequential Minimal Optimization (SMO).

A method of scrambling MPEG video by exchanging the motion vector (MV) in the MPEG bitstream is proposed. It deals directly with the MPEG bitstream and exclusive MPEG encoders are unnecessary. The size of the scrambled bitstream does not increase and image quality is maintained after descrambling. Moreover, the structure of the MPEG bitstream is maintained and can be decoded with a standard MPEG video decoder. We demonstrate the effectiveness of this method through simulation results that reveal unchanged image quality and size of bitstreams.

The proposed DOA (Direction Of Arrival) estimation method by integrating the frequency array data generated from microphone pairs in an equilateral-triangular microphone array is extended here. The method uses four microphones located at the apices of regular tetrahedron to enable to estimate the elevation angle from the array plane as well. Furthermore, we introduce an idea for separate estimation of azimuth and elevation to reduce the computational loads.

We newly propose a novel blind separation framework for Single-Input Multiple-Output (SIMO)-model-based acoustic signals using an extended ICA algorithm, SIMO-ICA. The SIMO-ICA consists of multiple ICAs and a fidelity controller, and each ICA runs in parallel under the fidelity control of the entire separation system. The SIMO-ICA can separate the mixed signals, not into monaural source signals but into SIMO-model-based signals from independent sources as they are at the microphones. Thus, the separated signals of SIMO-ICA can maintain the spatial qualities of each sound source. In order to evaluate its effectiveness, separation experiments are carried out under both nonreverberant and reverberant conditions. The experimental results reveal that the signal separation performance of the proposed SIMO-ICA is the same as that of the conventional ICA-based method, and that the spatial quality of the separated sound in SIMO-ICA is remarkably superior to that of the conventional method, particularly for the fidelity of the sound reproduction.

In this paper, we propose a resolution enhancement method for estimating direction-of-arrival (DOA) of narrowband incoherent signals incident on a general array. The resolution of DOA algorithm is dependent on the aperture size of antenna array. But it is very impractical to increase the physical size of antenna array in real environment. We propose the method that improves resolution performance by virtually expanding the sensor spacing of original antenna array and then averaging the spatial spectrum of each virtual array which has a different aperture size. Superior resolution capabilities achieved with this method are shown by simulation results in comparison with the standard MUSIC for incoherent signals incident on a uniform circular array.

In this article, it is shown that Unified Complex Hadamard Transform (UCHT) can be derived from Walsh functions and through direct matrix operation. Unique properties of UCHT are analyzed. Recursive relations through Kronecker product can be applied to the basic matrices to obtain higher dimensions. These relations are the basis for the flow diagram of a constant-geometry iterative VLSI hardware architecture. New Normalized Complex Hadamard Transform (NCHT) matrices are introduced which are another class of complex Hadamard matrices. Relations of UCHT and NCHT with other discrete transforms are discussed.

In a high-rate indoor wireless personal communication system, the delay spread due to multi-path propagation results in intersymbol interference which can significantly increase the transmission bit error rate (BER). The technique most commonly used for combating the intersymbol interference and frequency-selective fading found in communications channels is the adaptive equalization. In this paper, we propose a novel neural detector based on self-organizing map (SOM) to improve the system performance of the receiver. In the proposed scheme, the SOM is used as an adaptive detector of equalizer, which updates the decision levels to follow the received faded signal. To adapt the proposed scheme to the time-varying channel, we use the Euclidean distance, which will be updated automatically according to the received faded signal, as an adaptive radius to define the neighborhood of the winning neuron of the SOM algorithm. Simulations on a 16 QAM system show that the receiver using the proposed neural detector has a significantly better BER performance than the traditional receiver.

In this paper, we propose a new parallel algorithm for cellular radio channel assignment problem that can help the expanded maximum neural network escape from local minima by introducing a transient chaotic neurodynamics. The goal of the channel assignment problem, which is an NP-complete problem, is to minimize the total interference between the assigned channels needed to satisfy all of the communication needs. The expanded maximum neural model always guarantees a valid solution and greatly reduces search space without a burden on the parameter-tuning. However, the model has a tendency to converge to local minima easily because it is based on the steepest descent method. By adding a negative self-feedback to expanded maximum neural network, we proposed a new parallel algorithm that introduces richer and more flexible chaotic dynamics and can prevent the network from getting stuck at local minima. After the chaotic dynamics vanishes, the proposed algorithm then is fundamentally reined by the gradient descent dynamics and usually converges to a stable equilibrium point. The proposed algorithm has the advantages of both the expanded maximum neural network and the chaotic neurodynamics. Simulations on benchmark problems demonstrate the superior performance of the proposed algorithm over other heuristics and neural network methods.

All power electronic circuits with state feedback controlled switching can be described as nonlinear time-varying dynamical systems. The occurrence of chaos--where the ripple waveforms become aperiodic--is common in such systems. It is shown here that this natural phenomenon may be effectively used in minimizing electromagnetic interference problems in power electronic circuits. This is because converters operating chaotically tend to spread the spectrum, thereby reducing the interference power at any target frequency. We also present the ways of calculating the average values of state variables and the power spectrum under chaotic operation.

This paper proposes the design and implementation of a real-time image compressor using 2-Dimensional Discrete Wavelet Transform (2DDWT), which targets an FPGA as its platform. The image compressor uses Daubechies' bi-orthogonal DWT filters (9, 7) and 16-bit fixed-point data formats for wavelet coefficients in the internal calculation. The target image is NTSC 640240 pixels per field whose color format is Y:Cb:Cr = 4:2:2. We developed for the 2DDWT a new structure with four Multipliers and Accumulators (MACs) for real-time operations. We designed and used a linear fixed scalar quantizer, which includes the exceptional treatment of the coefficients whose absolute values are larger than the quantization region. Only a Huffman entropy encoder was included due to the hardware overhead. The quantizer and Huffman encoder merged into a single functional module. Due to the insufficient memory space of an FPGA, we utilized external memory (SDRAM) as the working and memory storage space. The proposed image compressor maps into an APEX20KC EP20K600CB652-7 from Altera and uses 45% of the Logic Array Block (LAB) and 9% of the Embedded System Block (ESB). With a 33 MHz clock frequency, the proposed image compressor shows a speed of 67 fields per second (33 frames per second), which is more than real-time operation. The resulting image quality from reconstruction is approximately 28 dB in PSNR and its compression ratio is 29:1. Consequently, the proposed image compressor is expected to be used in a dedicated system requiring an image-processing unit.

In order to produce precise enclosures from a multi-dimensional interval vector, we introduce a sharp interval sub-dividing condition for optimization algorithms. By utilizing interval inclusion properties, we also enhance the sampling of an upper bound for effective use in the interval quadratic method. This has resulted in an improvement in the algorithm for the unconstrained optimization problem by Hansen in 1992.

Montgomery-form elliptic curves have the advantage of faster arithmetic than Weierstrass-form elliptic curves. The dominant operation of the Elliptic Curve Cryptosystem (ECC) is scalar multiplication of points on an elliptic curve, and it usually includes scalar multiplication of a fixed base point of ECC. For Weierstrass-form elliptic curves, accelerating methods of scalar multiplication by using a pre-computed table of the fixed point have been widely studied. However, such methods cannot naturally expand to Montgomery-form elliptic curves. In this paper, we propose a fast scalar multiplication method on Montgomery-form elliptic curves by using a pre-computed table for the first time. Our method is 1.6 times as fast as the known method for Montgomery-form elliptic curves under the practical conditions that the size of the definition field is 160 bits and the memory size used for the pre-computed table is 3.2 KB.

A fast motion estimation algorithm is proposed, which performs a tree-structured motion vector search for variable blocks in the integer-pixel unit. The proposed method is based on the inequality of sum norms to find the best estimate of the motion vectors for variable blocks. The proposed motion estimation algorithm is applied to the Joint Video Team (JVT) encoder that performs variable-block motion estimation (ME) with quarter-pixel unit. In terms of computational complexity, the proposed motion estimation algorithm searches motion vectors about 10.7 times as fast as the spiral full search with early termination and 6.6 times as fast as the fast full search using the hierarchical sum of absolute difference (SAD), while the PSNR (peak signal-to-noise ratio) of the reconstructed image is slightly degraded.

In terms of the formulation of the optimality, image restoration filters can be divided into two streams. One is formulated as an optimization problem in which the fidelity of a restored image is indirectly evaluated, and the other is formulated as an optimization problem based on a direct evaluation. Originally, the formulation of the optimality and the solutions derived from the formulation are identical each other. However in many studies adopting the former stream, an arbitrary choice of a solution without a mathematical ground passes unremarked. In this paper, we discuss the relation between the formulation of the optimality and the solution derived from the formulation from a mathematical point of view, and investigate the relation between a direct style formulation and an indirect one. Through these analyses, we show that the both formulations yield the identical filter in practical situations.

In this paper, we will propose a robust watermarking system for digital audio sound to protect the copyright of publication and claim of ownership. The proposed watermarking scheme uses the frequency extent between 1 Hz and 20 Hz, which cannot be heard by the unaided human ear, to embed the watermark. Thus, the original audio quality will not be influenced by the watermark. Currently, the techniques of Perceptual Audio Coder contain MPEG-1, -2, -2.5, MPEG-2 AAC, MPEG-4 AAC and Window Media Audio. From experimental results, the proposed watermarking system can resist attacks of previous audio coders and low bit-rate compression. The watermark is extracted with 100% correction after previous encoder attacks. Furthermore, to authenticate the audio signal, the system can quickly extract the watermark without the knowledge of original audio signals.

A new algorithm, termed reduced-order Root-MUSIC, for high resolution direction finding is proposed. It requires finding all the roots of a polynomial with an order equaling twice the number of propagating signals. Some Monte Carlo simulations are used to test the effectiveness of the proposed algorithm.

A simple adaptive internal model control structure is designed and tested on the real-time temperature control of a process. The design procedure remains same for both minimum and non-minimum phase systems. The effect of the process zeros on the output is compensated by using adaptive finite impulse response filters. This guarantees the stability of the closed-loop.

This paper deals with a design problem of an adaptive robust control system for linear systems with structured uncertainties. The control law consists of a state feedback with a fixed gain designed by using the nominal system, a state feedback with an adaptive gain tuned by a parameter adjustment law and a compensation input. We show the parameter adjustment law and that sufficient conditions for the existence of the compensation input are given in terms of linear matrix inequalities (LMIs). Finally, a numerical example is included.

In this article, we will present a modification attack and a dictionary attack to subvert the security of the Tseng scheme and the Ku-Wang scheme. As we know, no existing schemes of simple authenticated key agreement protocols can successfully withstand our modification attack.

In 2003, Wu proposed a threshold access control scheme based on smart cards. In this letter, we show that the scheme is vulnerable to various attacks.

In this letter, we indicate that a proposed user-friendly remote authentication scheme with smart card is insecure. The authentication scheme suffers from the replay attack. An adversity can eavesdrop valid authentication information from the communicating data, modify it, and impersonate the legitimate user to login the remote system. We also present a modified scheme to overcome this vulnerability and improve the robustness. In the modified scheme, the replay attack cannot work successfully. To crack the password from the communicating message is infeasible. Even if the password is compromised, the attacker still cannot pass the authentication and gain the authority of the legitimate user.

In this letter, some more concrete trellis relations between a lattice and its dual lattice are firstly given. Based on these relations, we generalize the main results of [1].

This letter studies the impact of chip waveform shaping on the multiple access interference (MAI) in band-limited direct sequence code-division multiple access (DS-CDMA) systems. The family of band-limited waveforms with zero interchip interference (ICI) and with an excess bandwidth β in the range 0β 1 is considered. A criterion for the performance comparison of various band-limited chip waveforms based on the elementary density function is established. The effect of varying the roll-off factor of a band-limited chip waveform on the MAI level is also investigated.

This paper analyzes the timing of eyeblink during visual identification of katakana characters on a display, which were presented under the constraint of a restricted visual field (R.V.F.). Blinks frequently occurred when the subject slowly brought the R.V.F. near a feature point (e.g., terminal point, crossing point).