This paper presents a maximum likelihood (ML) identification and restoration method for noisy blurred images. The unitary discrete sine transform (DST) is employed to decouple the large order spatial state-space representation of the noisy blurred image into a bank of one-dimensional real state-space scalar subsystems. By assuming that the noises are Gaussian distributed processes, the maximum likelihood estimation technique using the expectation-maximization (EM) algorithm is developed to jointly identify the blurring functions, the image model parameters and the noise variances. In order to improve the computational efficiency, the conventional Kalman smoother is incorporated to give the estimates. The identification process also yields the estimates of transformed image data, from which the original image is restored by the inverse DST. The experimental results show the effectiveness of the proposed method and its superiority over the recently proposed spatial domain DFT-based methods.

This paper describes an ultra low power, motion estimation (ME) processor for MPEG2 HDTV resolution video. It adopts a Gradient Descent Search (GDS) algorithm that drastically reduces required computational power to 6 GOPS. A SIMD datapath architecture optimized for the GDS algorithm decreases the clock frequency and operating voltage. A low power 3-port SRAM with a write-disturb-free cell array arrangement is newly designed for image data caches of the processor. The proposed ME processor contains 7-M transistors, integrated in 4.50 mm 3.35 mm area using 0.13 µm CMOS technology. Estimated power consumption is less than 100 mW at 81 MHz@1.0 V. The processor is applicable to a portable HDTV system.

This letter presents a Monte-Carlo FDTD technique to determine the scattered field from a perfectly conducting fractal surface from which the useful information on the incoherent pattern tendency could be observed. A one-dimensional fractal surface was generated by the bandlimited Weierstrass function. In order to verify the numerical results by this technique, these results are compared with those of Kirchhoff approximations, which show a good match between them. To investigate the incoherent pattern tendency involved, the dependence of the fitting curve slope on the different D and is discussed for the bistatic and back scattering case, respectively.

A high efficient HBT MMIC power amplifier with a new on-chip bias control circuit was proposed for PCS applications. By adjusting the quiescent current in accordance with the output power levels, the average power usage efficiency of the power amplifier is improved by a factor of 1.4. The bias controlled power amplifier, depending on low (high) output power levels, shows 62(103) mA of quiescent current, 16(28) dBm output power with 7.5(35.4)% of power-added efficiency(PAE), -46(-45) dBc of adjacent-channel power ratio (ACPR), and 23.7(26.9) dB of gain

An 8-bit 200 MS/s CMOS 2-stage cascaded folding/interpolating ADC chip was implemented by applying a resistor averaging/interpolating scheme at the preamplifier outputs and the differential circuits for the encoder logic block, with a 0.35-µm double-poly CMOS process. The number of preamplifiers was reduced to half by using an averaging technique with a resistor array at the preamplifier outputs. The delay time of digital encoder block was reduced from 2.2 ns to 1.3 ns by replacing the standard CMOS logic with DCVSPG and CPL differential circuits. The measured SFDR was 42.5 dB at the sampling rate of 200 MS/s for the 10.072 MHz sinusoidal input signal.

A wavelet-based vector quantization scheme for image compression is introduced here. The proposed scheme obtains a better compression efficiency by the following three methods. (1) Utilizing the correlation among wavelet coefficients. (2) Placing different emphasis on wavelet coefficients at different levels. (3) Preserving the most important information of the image. In our experiments, simulation results show that this technique outperforms the recent SMVQ-ABC [1] and WTC-NIVQ [2] techniques.

Several lifting implementation techniques for invertible deniterlacing are proposed in this paper. Firstly, the invertible deinterlacing is reviewed, and an efficient implementation is presented. Next, two deinterlacer-embedded lifting architectures of discrete wavelet transforms (DWT) is proposed. Performances are compared among several architectures of deinterlacing with DWT. The performance evaluation includes dual-multiplier and single-multiplier architectures. The number of equivalent gates shows that the deinterlacing-embedded architectures require less resources than the separate implementaion. Our experimental evaluation of the dual-multiplier architecture results in 0.8% increase in the gate count, whereas the separate implementation of deinterlacing and DWT requires 6.1% increase from the normal DWT architecture. For the proposed single-multiplier architecture, the gate count is shown to result in 4.5% increase, while the separate counterpart yields 10.7% increase.

A heterogeneous parallel computing environment consisting of different types of workstations and communication links plays an important role in parallel computing. In many applications on the system, collective communication operations are commonly used as communication primitives. Thus, design of the efficient collective communication operations is the key to achieve high-performance parallel computing. But the heterogeneity of the system complicates the design. In this paper, we consider design of an efficient gather operation, one of the most important collective operations. We show that an optimal gather schedule is found in O(n2k-1) time for the heterogeneous parallel computing environment with n processors of k distinct types, and that a nearly-optimal schedule is found in O(n) time if k=2.

The paper is concerned with an identification-based predistortion scheme for compensating nonlinearity of high power amplifiers (HPA). The identification algorithms for the Wiener-Hammerstein nonlinear model are developed in the frequency domain. By approximately modeling the nonlinear distortion part in HPA by polynomial or spline functions, and introducing linear distortion parts in the input and output of the nonlinear element, the iterative identification schemes are proposed to estimate all the uncertain parameters and to construct an inverse system for the predistortion.

This paper presents an observer design methodology for a special class of MIMO nonlinear systems. First, we characterize the class of MIMO nonlinear systems that consists of the linear observable part and the nonlinear part with a block triangular structure. Also, the similarity transformation that plays an important role in proving the convergence of the proposed observer is generalized to MIMO systems. Since the gain of the proposed observer minimizes a nonlinear part of the system to suppress for the stability of the error dynamics, it improves the transient performance of the high gain observer. Moreover, by using the generalized similarity transformation, it is shown that under some observability and boundedness conditions, the proposed observer guarantees the global exponential convergence to zero of the estimation error. Finally, the simulation results for induction motor are included to illustrate the validity of our design scheme.

In a previous study about a combinatorial optimization problem solver using neural networks, since the Hopfield method, convergence to the optimum solution sooner and with more certainty is regarded as important. Namely, only static states are considered as the information. However, from a biological point of view, dynamical systems have attracted attention recently. Therefore, we propose a "dynamical" combinatorial optimization problem solver using hysteresis neural networks. In this paper, the proposed system is evaluated by the N-Queen problem.

A method of error concealment for JPEG2000 images is proposed in this paper. The proposed method uses the layer structure that is a feature of the JPEG2000. The most significant layer is hidden in the lowest layer of the JPEG2000 bit stream, and this embedded layer is used for error concealment. The most significant layer is duplicated because JPEG2000 uses bit-plane coding. In this coding, when the upper layers are affected by errors, the coefficients of the lower layers become meaningless. A bit stream encoded using the proposed method has the same data structure as a standard JPEG2000. Therefore, it can be decoded by a standard decoder. Our simulation results demonstrated the effectiveness of the proposed method.

In this paper, we propose two channel allocation schemes for supporting voice and multimedia traffic in hierarchical cellular systems. They are guaranteed to satisfy the required quality of service for multimedia traffic in accordance with their characteristics such as a mobile velocity for voice calls and a delay tolerance for multimedia calls. In the first, only slow-speed voice calls are allowed to overflow from macrocell to microcell and only adaptive multimedia calls can overflow from microcell to macrocell after reducing their bandwidth to the minimum channel bandwidth. In the second, in addition to the first scheme, non-adaptive multimedia calls can occupy the required channel bandwidth through reducing the channel bandwidth of adaptive multimedia calls. The proposed schemes are analyzed using the 2-dimensional Markov model. Through computer simulations, it is shown that the proposed schemes yield a significant improvement in terms of the forced termination probability of handoff calls. In particular, the second decreases the blocking probability of new calls as well as the forced termination probability of handoff calls.

This paper presents a BER performance derivation considering imperfect channel estimation for a pilot-aided coherent forward link of W-CDMA system under multipath Rayleigh fading channels. In the forward link of the W-CDMA system, pilot signal is usually used for coherent demodulation. In this paper, the maximum likelihood estimator, Wiener filter, and moving average filter are applied to estimate the channel effect due to mobile speed and frequency offset. Then, we concentrate on determining optimal parameter values of the estimators such as the observation length, delay parameters for causal/non-causal filter, and filter resolution. Also it is verified that these parameters are closely associated with the performance, hardware complexity, and characteristics of OVSF code. In particular, effect of data rate and filter resolution on the BER performance is analyzed in more detail. In addition, we show the performance comparison between the estimators considering various imperfections. Finally, we verify the derived BER by using an extensive Monte-Carlo computer simulation.

In this letter, we propose a new technique that reduces the computation time to derive the MEI coefficients in solving scattering problems by the Measured Equation of Invariance (MEI) methods. Methods that use the MEI technique spend most of the computation time in the integration process to derive the MEI coefficients. Moreover, in the conventional solution process, some repeated computation of metron fields to derive the MEI coefficients is included. To avoid the repeated operations and thus save computation time, we propose a matrix localization technique in computing the MEI coefficients. The time comparison for the computation of MEI coefficients of a cylinder and a sphere is given to verify the CPU time reduction of our new technique.

This paper investigates a new method for creating robust speaker models to cope with inter-session variation of a speaker in a continuous HMM-based speaker verification system. The new method estimates session-independent parameters by decomposing inter-session variations into two distinct parts: session-dependent and -independent. The parameters of the speaker models are estimated using the speaker adaptive training algorithm in conjunction with the equalization of session-dependent variation. The resultant models capture the session-independent speaker characteristics more reliably than the conventional models and their discriminative power improves accordingly. Moreover we have made our models more invariant to handset variations in a public switched telephone network (PSTN) by focusing on session-dependent variation and handset-dependent distortion separately. Text-independent speech data recorded by 20 speakers in seven sessions over 16 months was used to evaluate the new approach. The proposed method reduces the error rate by 15% relatively. When compared with the popular cepstral mean normalization, the error rate is reduced by 24% relatively when the speaker models were recreated using speech data recorded in four or more sessions.

In this paper, we propose an instruction encoding scheme to reduce power consumption of instruction ROMs. The power consumption of the instruction ROM strongly depends on the switching activity of bit-lines due to their large load capacitance. In our approach, the binary-patterns to be assigned as op-codes are determined based on the frequency of instructions in order to reduce the number of bit-line dis-charging. Simulation results show that our approach can reduce 40% of bit-line switchings from a conventional organization.

The paper overviews and surveys Japan's reflector antennas for earth stations and radio telescopes since the 1960's. Some interferometers for radio astronomy are included. Japanese original technologies regarding reflector antenna design and measurement are also described. There are 35 figures and 3 tables.

One of the biggest limitations of BP algorithm is its low rate of convergence. The Variable Learning Rate (VLR) algorithm represents one of the well-known techniques that enhance the performance of the BP. Because the VLR parameters have important influence on its performance, we use learning automata (LA) to adjust them. The proposed algorithm named Adaptive Variable Learning Rate (AVLR) algorithm dynamically tunes the VLR parameters by learning automata according to the error changes. Simulation results on some practical problems such as sinusoidal function approximation, nonlinear system identification, phoneme recognition, Persian printed letter recognition helped us better to judge the merit of the proposed AVLR method.

This paper evaluates an on-line incremental speaker adaptation method for co-channel conversation including multiple speakers with the assumption that the speaker is unknown and changes frequently. After performing the speaker clustering treatment based on the Vector Quantization (VQ) distortion for every utterance, acoustic models for each cluster are adapted by Maximum Likelihood Linear Regression (MLLR) or Maximum A Posteriori probability (MAP). The performance of continuous speech recognition could be improved. In this paper, to prove the efficiency of the speaker clustering method for improving the performance of continuous speech recognition, the continuous speech recognition experiments with supervised and unsupervised cluster adaptation were conducted, respectively. Finally, evaluation experiments based on other prepared test data were performed on continuous syllable recognition and large vocabulary continuous speech recognition (LVCSR). The efficiency of the speaker adaptation and clustering methods presented in this paper was supported strongly by the experimental results.