The objective of this study was to explore suitable spatial filters for inverse estimation of cortical potentials from the scalp electroencephalogram. The effect of incorporating noise covariance into inverse procedures was examined by computer simulations. The parametric projection filter, which allows inverse estimation with the presence of information on the noise covariance, was applied to an inhomogeneous three-concentric-sphere model under various noise conditions in order to estimate the cortical potentials from the scalp potentials. The present simulation results suggest that incorporation of information on the noise covariance allows better estimation of cortical potentials, than inverse solutions without knowledge about the noise covariance, when the correlation between the signal and noise is low. The method for determining the optimum regularization parameter, which can be applied for parametric inverse techniques, is also discussed.

This letter investigates the peak-to-average power ratio (PAR) reduction scheme employing a simple symbol transform in OFDM-CDMA systems. This approach is very simple because of no additional complexity and works with arbitrary numbers of subcarriers and without restriction on the allocation of spreading code, maintaining an original transmission efficiency. Simulation results show that the investigated scheme gives the PAR reduction gain of 2-3 dB compared to the original OFDM and OFDM-CDMA signals, and can provide the further PAR reduction by combing the partial transmit sequence (PTS) scheme, which is less complex compared to the ordinary PTS approach.

Within a few years it will be possible to integrate a billion transistors on a single chip operating at frequency more than 10 GHz. At this integration level, we propose using a multi-level ISA to express fine-grain data parallelism to hardware instead of using a huge transistor budget to dynamically extract it. Since the fundamental data structures for a wide variety of data parallel applications are scalar, vector, and matrix, our proposed Trident processor extends a scalar ISA with vector and matrix instruction sets to effectively process matrix formulated applications. Like vector architectures, the Trident processor consists of a set of parallel lanes (each lane contains a set of vector pipelines and a slice of register file) combined with a fast scalar core. However, Trident processor can effectively process on the parallel lanes not only vector but also matrix data. One key point of our architecture is the local communication within and across lanes to overcome the limitations of the future VLSI technology. Another key point is the effective execution of a mixture of scalar, vector, and matrix operations. This paper describes the architecture of the Trident processor and evaluates its performance on BLAS and on the standard matrix bidiagonalization algorithm. The last one is evaluated as an example of an entire application based on a mixture of scalar, vector, and matrix operations. Our results show that many data parallel applications, such as scientific, engineering, multimedia, etc., can be speeded up on the Trident processor. Besides, the scalability of the Trident processor does not require more fetch, decode, or issue bandwidth, but requires only replication of parallel lanes.

There have been numerous studies on the enhancement of the noisy speech signal. In this paper, we propose a completely new speech enhancement method, that is, a filtering of a dissonant frequency based on improved fundamental frequency estimation which is developed in frequency domain. The subjective test results indicate that the proposed method provides a significant gain in audible improvement especially for speech contaminated by colored noise and a husky voice. Therefore if the filter is employed as a pre-filter for speech enhancement, the output speech quality and intelligibility should be greatly enhanced.

This paper proposes a novel extraction method of line parameters for multi-coupled lines on high-speed and high-density PCBs, where it uses TDR measurement in time domain and S-parameter measurement in frequency domain. The accuracy of the proposed method have been verified experimentally by comparing the crosstalk noise in the time domain, where (1) the proposed method extracts RLGC matrices by measuring the test pattern, (2) the crosstalk noise is obtained through SPICE simulation using the extracted RLGC matrices, and (3) the SPICE-simulated crosstalk noise is compared with the measured crosstalk noise. From the crosstalk noise comparison, the proposed method is proven to be very accurate. For N-coupled lines, the proposed method doesn't require expensive 2N-port probe for N-coupled lines but only two-port probe, which provides a simple, accurate, and economic extraction method of line parameters for multi-coupled line on the PCB. In the early stage of PCB design, the proposed method is very useful, because it extracts accurate interconnection parameters of each test board and enables to compensate various side effects due to the variation of PCB fabrication process. Also, the proposed method is necessary to analyze the signal integrity of future high-density and high-speed digital system on PCBs.

Passification of a non-square linear system is considered by using a parallel feedforward compensator (PFC) and a squaring gain matrix. In contrast to the previous result, a technical assumption is removed by modifying the structure of the PFC. As a result, the broader class of non-square systems can be made passive by the proposed design method. Using the static output feedback (SOF) algorithms, the input-dimensional PFC and the squaring matrix can be designed systematically. The effectiveness of the proposed method is illustrated by practical system examples in the control literature.

We newly propose a stable algorithm for blind source separation (BSS) combining multistage ICA (MSICA) and linear prediction. The MSICA is the method previously proposed by the authors, in which frequency-domain ICA (FDICA) for a rough separation is followed by time-domain ICA (TDICA) to remove residual crosstalk. For temporally correlated signals, we must use TDICA with a nonholonomic constraint to avoid the decorrelation effect from the holonomic constraint. However, the stability cannot be guaranteed in the nonholonomic case. To solve the problem, the linear predictors estimated from the roughly separated signals by FDICA are inserted before the holonomic TDICA as a prewhitening processing, and the dewhitening is performed after TDICA. The stability of the proposed algorithm can be guaranteed by the holonomic constraint, and the pre/dewhitening processing prevents the decorrelation. The experiments in a reverberant room reveal that the algorithm results in higher stability and separation performance.

A nonlinear combiner random number generator is a general keystream generator for certain stream ciphers. The generator is composed of several linear feedback shift registers and a nonlinear function; the output is used as a keystream. A fast correlation attack is a typical attack for such keystream generators. Mihaljevi, Fossorier, and Imai have proposed an improved fast correlation attack. The attack is based on error correction of information bits only in the corresponding binary linear block code; APP threshold decoding is employed for the error correction procedure. In this letter, we propose a method which improves the success rate of their attacks with similar complexity. The method adds some intentional error to original parity check equations. Those equations are then used in APP threshold decoding.

A robust adaptive filtering algorithm was established recently (I. Yamada, K. Slavakis, K. Yamada 2002) based on the interactive use of statistical noise information and the ideas developed originally for efficient algorithmic solutions to the convex feasibility problems. The algorithm is computationally efficient and robust to noise because it requires only an iterative parallel projection onto a series of closed half spaces highly expected to contain the unknown system to be identified and is free from the computational load of solving a system of linear equations. In this letter, we show the potential applicability of the adaptive algorithm to the identification problem for the second order Volterra systems. The numerical examples demonstrate that a straightforward application of the algorithm to the problem soundly realizes fast and stable convergence for highly colored excited speech like input signals in possibly noisy environments.

We present a physics-based circuit simulator employing the Monte Carlo (MC) particle technique, which serves as a bridge between the small-device physics and the circuit designs. Two different geometries of GaAs-MESFET's are modeled and analyzed by the simulator. The Y-parameters of the devices are extracted from the transient currents, and then translated into the S-parameters. The cut-off frequency (fT) is estimated from the Y-parameters. The minimum noise figure (Fmin) is also estimated by evaluating the fluctuation in the stationary current. The device, having the n+-region placed just at the drain side of the gate, exhibits the better performances in both fT and Fmin. The analysis on the equivalent circuit (EC) elements reveals that its better performances are mainly due to the reduced gate-source capacitance (Cgs) and the increased transconductance (gm0), which result from the shortened effective gate length (Lg) caused by the termination of the depletion region at the gate edge. The termination of the depletion region, however, causes the increase of the electric field, which results in the higher heat generation rate near the gate edge. It is proven that the physics-based circuit simulator developed here is fully effective to see the inside of the small-device and to model it for the millimeter-wave circuit design.

This paper presents an even harmonic mixer using self-biased anti-parallel diode pair (APDP). A proposed self-biased APDP is composed of a pair of diodes and self-bias series resistors. At high LO injection level, rectified current is generated by the diodes and reverse voltage is applied to the diodes by the self-bias resistor. Therefore, rapid degradation of conversion loss at high LO input level can be avoided. The effect of self-bias resistor is explained by using simplified behavior model and harmonic balance method, and is evaluated by the measurements of an L-band even harmonic type direct conversion mixer.

We propose a scheme for the design of irregular low-density parity-check (LDPC) codes based on Euclidian Geometry using Latin square matrices of random sequence. Our scheme is a deterministic method that allows the easy design of good irregular LDPC codes for any code rate and degree distribution. We optimize the LDPC codes using the Gaussian approximation method. A Euclidean Geometry LDPC code (EG-LDPC) is used as the basis for the construction of an irregular LDPC code. The base EG-LDPC code is extended by splitting rows and columns using a table of Latin square matrices of random sequence to determine the edges along which to split. We provide simulation results for codes constructed in this manner evaluated in terms of bit error rate (BER) performance in AWGN channels. We believe that our scheme is superior in terms of computational requirements and resulting BER performance in comparison to creation of irregular LDPC codes by means of random construction using a search algorithm to exclude cycles of length four.

In 2002, Hwang, Lee, and Lai presented an attack on the untraceability property of Fan and Lei's partially blind signature scheme. In this letter, their attack is demonstrated as being invalid.

An adaptive blind signal separation filter is proposed using a risk-sensitive criterion framework. This criterion adopts an exponential type function. Hence, the proposed criterion varies the consideration weight of an adaptation quantity depending on errors in the estimates: the adaptation is accelerated when the estimation error is large, and unnecessary acceleration of the adaptation does not occur close to convergence. In addition, since the algorithm derivation process relates to an H filtering, the derived algorithm has robustness to perturbations or estimation errors. Hence, this method converges faster than conventional least squares methods. Such effectiveness of the new algorithm is demonstrated by simulation.

This paper describes two methods to construct fuzzy inference rules by the simplified fuzzy reasoning. The present methods have a construction mechanism of the rule unit that is applicable in two parameters: the central value and the width of the membership function in the antecedent part. The first approach is to create a rule unit near the selected rule which has the nearest position from the central input space for the central value. The second is to create a rule unit near the selected rule which has the minimum width for the width. Experimental results are presented in order to show that the proposed methods are effective in difference on the inference error and the number of learning iterations.

In this paper, we propose an efficient requantization method for transcoding of MPEG video. Transcoding is the process of converting a compressed video format to another different compressed video format. We propose an simple and efficient transcoding by requantization in which MPEG coded video at high bit-rate is converted into MPEG bitstream at lower bit-rate. To reduce a image quality degradation, we use HVS (Human Visual System). By using this effect, the part of image in high activity region is coarsely quantized without seriously degrading the image quality. Experimental results show that the proposed method can provide good performance.

Utilizing a macromodel which calculates the floating gate potential by combining resistances and dependent voltage and current sources, DC transfer characteristics for multi-input neuron MOS inverters and for those in the neuron MOS full adder circuit are simulated both at room temperature and at 77 K. Based on the simulated results, low temperature circuit failures are discussed. Furthermore, circuit design parameter optimization both for low and room temperature operations is described.

Many feature tracking algorithms have been proposed for motion segmentation, but the resulting trajectories are not necessarily correct. In this paper, we propose a technique for removing outliers based on the knowledge that correct trajectories are constrained to be in a subspace of their domain. We first fit an appropriate subspace to the detected trajectories using RANSAC and then remove outliers by considering the error behavior of actual video tracking. Using real video sequences, we demonstrate that our method can be applied if multiple motions exist in the scene. We also confirm that the separation accuracy is indeed improved by our method.

A simple modeling technique for symmetric inductors is proposed. Using the proposed technique, all model parameters for an equivalent circuit of symmetric inductors are easily calculated from geometric, process and substrate resistance parameters without using electromagnetic (EM) simulators. Comparison of simulated results with measured results verifies the effectiveness of the proposed modeling technique up to 5 GHz with center-tapped or non-center-tapped configurations.

The equidistortion principle[1] has recently been proposed as a basic principle for design of an optimal vector quantization (VQ) codebook. The equidistortion principle adjusts all codebook vectors such that they have the same contribution to quantization error. This paper introduces a novel VQ codebook design algorithm based on the equidistortion principle. The proposed algorithm is a variant of the law-of-the-jungle algorithm (LOJ), which duplicates useful codebook vectors and removes useless vectors. Due to the LOJ mechanism, the proposed algorithm can establish the equidistortion condition without wasting learning steps. This is significantly effective in preventing performance degradation caused when initial states of codebook vectors are improper to find an optimal codebook. Therefore, even in the case of improper initialization, the proposed algorithm can achieve minimization of quantization error based on the equidistortion principle. Performance of the proposed algorithm is discussed through experimental results.