Reduction of the complexity of the NLMS algorithm has received attention in the area of adaptive filtering. A processing cost reduction method, in which the component of the weight vector is updated when the absolute value of the sample is greater than or equal to the average of the absolute values of the input samples, has been proposed. The convergence analysis of the processing cost reduction method has been derived from a low-pass filter expression. However, in this analysis the effect of the weignt vector components whose adaptations are skipped is not considered in terms of the direction of the gradient estimation vector. In this paper, we use an arbitrary value instead of the average of the absolute values of the input samples as a threshold level, and we derive the convergence characteristics of the processing cost reduction method with arbitrary threshold level for zero-mean white Gaussian samples. From the analytical results, it is shown that the range of the gain constant to insure convergence and the misadjustment are independent of the threshold level. Moreover, it is shown that the convergence rate is a function of the threshold level as well as the gain constant. When the gain constant is small, the processing cost is reduced by using a large threshold level without a large degradation of the convergence rate.

We present distributed load balancing mechanisms implemented on multiprocessor systems for real time video encoding, which dynamically equalize load amounts among PE's to cope with extensive computing requirements. The loosely coupled multiprocessor system, e.g. a torus connected one, is treated as the objective system. Two decentralized controlled load balancicg algorithms are proposed, and mathematical analyses are provided to obtain some insights of our decentralized controlled mechanisms. We also prove the proposed algorithms are steady and effective theoretically and experimentally.

We develop a convergence theory of the simple genetic algorithm (SGA) for two-bit problems (Type I TBP and Type II TBP). SGA consists of two operations, reproduction and crossover. These are imitations of selection and recombination in biological systems. TBP is the simplest optimization problem that is devised with an intention to deceive SGA into deviating from the maximum point. It has been believed that, empirically, SGA can deviate from the maximum point for Type II while it always converges to the maximum point for Type I. Our convergence theory is a first mathematical achievement to ensure that the belief is true. Specifically, we demonstrate the following. (a) SGA always converges to the maximum point for Type I, starting from any initial point. (b) SGA converges either to the maximum or second maximum point for Type II, depending upon its initial points. Regarding Type II, we furthermore elucidate a typical sufficient initial condition under which SGA converges either to the maximum or second maximum point. Consequently, our convergence theory establishes a solid foundation for more general GA convergence theory that is in its initial stage of research. Moreover, it can bring powerful analytical techniques back to the research of original biological systems.

This paper proposes a fast convergence algorithm for adaptive FIR filters with sparse taps. Coefficient values and positions are simultaneously controlled. The proposed algorithm consists of two stages： flat-delay estimation and tapposition control with a constraint. The flat-delay estimation is carried out by estimating the significant dispersive region of the impulse response. The constrained tap-position control is achieved by imposing a limit on the new-tap-position search. Simulation results show that the proposed algorithm reduces the convergence speed by up to 85% over the conventional algorithms for a white signal input. For a colored signal, it also converges in 40% of the convergence time by the conventional algorithms. The proposed algorithm is applicable to adaptive FIR filters which are to model a path with long flat delay, such as echo cancelers for satellite-link communications.

This paper proposes new algorithms for adaptive FIR filters. The proposed algorithms provide both fast convergence and small final misadjustment with an adaptive step size even under an interference to the error. The basic algorithm pays special attention to the interference which contaminates the error. To enhance robustness to the interference, it imposes a special limit on the increment/decrement of the step-size. The limit itself is also varied according to the step-size. The basic algorithm is extended for application to nonstationary signals. Simulation results with white signals show that the final misadjustment is reduced by up to 22 dB under severe observation noise at a negligible expense of the convergence speed. An echo canceler simulation with a real speech signal exhibits its potential for a nonstationary signal.

Impact ionization () in two n+-n--n+ device structures is investigated. Data obtained from self-consistent Monte-Carlo (SCMC) simulations of the devices is used to show that the average energy () of only those high energy electrons contributing to is an appropriate variable for the modeling of . A transport model allowing one to calculate is derived from the Boltzmann transport equation (BTE) and calibrated by the SCMC simulation results. The values of and the coefficient, αii, predicted by the proposed model are in good agreement with the Monte-Carlo data.

An efficient method which integrates a 2-D energy transport model, impact ionization model, gate current model, a discretized gate-capacitor EPROM model, and a post-processing quasi-transient programming/erase method, was developed for deep-submicron EPROM/Flash device simulation. The predicted results showed on the average better than 90% accuracy, and it took only few minutes CPU time on a SUN/SPARC2 to generate EPROM/Flash Vt shift curves.

A two-dimensional quasi-exact active imaging method for detecting the conducting objects buried in a dielectric half-space is proposed. In this imaging method, an image function which is a projection of buried object to an arbitrary direction, is introduced exactly by taking account of the presence of the planar boundary. The image function is synthesized from the scattering fields which are measured by moving a transmitting antenna (a current source) and a receiving antenna (an observation point) simultaneously along the ground surface. The scattering field is generated by the physical optics current assumed on the surface of buried object. Because the effectiveness of physical optics approximation has been confirmed for this problem, this is a quasi-exact active imaging method. The validity of this imaging method is confirmed by some numerical simulations and an experiment.

This paper presents an equation capable of briefly evaluating the length of white noise sequence to be sent as a training signal. The equation is formulated by utilizing the formula describing the convergence property, which has been derived from the IIR filter expression of the NLMS algorithm. The result revealed that the length is directly proportional to I/[K(2-K)] where K is a step gain and I is the number of the adaptive filter taps.

This paper describes a new single-unit underground radar for detecting underground buried pipes. The pipe depth can be calculated from the hyperbolic shape in the cross-sectional image of radar echoes. The edge contour of the image is extracted, and the buried depth is judged from the similarity between the extracted hyperbolic curve and the theoretical curve. A suitable amplification rate is estimated by choosing the best image from numerous cross-sectional images formed during one antenna movement repeated at different amplification rates. The best image has few pixels corresponding to weak and saturated signals. The new radar is very compact, so it can be operated by one person. Objects buried up to 2.0m deep can be detected.

An FM-CW radar system for the detection of objects buried in sandy ground is explored and is applied to a field measurement. The key factors for underground FM-CW radar performance are the center frequency and bandwidth determining the depth at which the radar can detect targets and the resolution in the range direction. In order for FM-CW radar sounding, two ridged horn antennas are employed in the system, which are operative in the frequency range of 250-1000MHz. The impedance matching to the ground is optimized by measuring the echo strength from a fixed target as a function of the spacing interval between the antenna aperture and the ground surface. It is shown that the radar with an output power of 18dBm could detect a metallic plate (30100cm) and a pipe (10cmφ) buried at the depth of 1.2m. Also the synthetic aperture technique together with an averaging and subtracting method produced fine image in shallow region up to 100cm in the sandy ground.

Radar imaging technique is one of the most powerful tool for underground detection. However, performance of conventional methods is not sufficiently high when the observational direction or the aperture size is restricted. In the present paper, an image reconstruction method based on a model fitting with nonlinear least-squares has been developed, which is applicable to arbitrarily arranged arrays. Reconstruction is executed on the assumption that targets consist of discrete point scatterers embedded in a homogeneous medium. Model fitting is iterated as the number of point target in the assumed model is increased, until the residual in fitting becomes unchanged or small enough. A penalty function is used in nonlinear least-squares to make the algorithm stable. Fundamental characteristics of the method revealed with computer simulation are described. This method focuses a much sharper image than that obtained by the conventional aperture synthesis technique.

To clarify the stereopsis disturbance in patients with Alzheimer's disease (AD), we analyzed binocular eye movement when subjects shifted their gaze between targets at different depths. Subjects are patients with Alzheimer's disease, Mluti-infarct dementia (MID), or Olivopontocerebellar atrophy (OPCA), and healthy controls. Targets are arranged in two ways: along the median plane and asymmetrically crossing the median plane, at distances from the eyes of 1000 mm and 300 mm. When the targets are switched at the onset of a beep, the subjects shifted their gaze to the lit target. The experiment is conducted in a dimly lit room whose structure is capable of providing good binocular cues for depth. In AD subjects, especially in the subjects whose symptoms are moderate (advanced stage), vergence is limited and the change in the convergence angle is small, unstable, and non-uniform. These results are different from those of other patients (MID) and OPCA) or healthy controls and suggest a disturbance of stereopsis in the parietal lobe where AD patients typically have dysfunctions.

A simple method is given for obtaining new families of pseudonoise (PN) sequences based on chaotic non-linear maps. Such families are worse than the Gold and the Kasami families in terms of maximum correlation values. Nevertheless, such a method has several advantages: the generation is easy, and various families with an arbitrary family size and sequence period can be obtained primarily because non-linear maps have several parameters to be secret keys for communications security. Hence these sequences are good candidates of spreading sequences for CDMA.

In this letter, a new structure of adaptive IIR notch filter is presented. The structure is based on direct form realization and uses the similar adaptation algorithm given in Ref. (4). A quantitative analysis for convergence properties is developed. It is shown that the proposed structure shows superior performance comparing with previously proposed designs. The results of computer simulations are presented to substantiate the analysis.

Numerical solutions for the near-field of microstrip antennas are presented. The field distribution is calculated by taking the inverse Fourier transform involving the current distribution with the help of the spectral-domain moment method. A new technique to save the computation time is devised, and the field pattern of the circularly polarized antenna is illustrated.

In this paper, we present an efficient method for the fault simulation of the reconvergent fan-out stem. Our method minimizes the fault propagating region by analyzing the topology of the circuit, whose region is smaller than that of Tulip's. The efficiency of our method is illustrated by experimental results for a set of benchmark circuits.

The most commonly used activation function in Backpropagation learning is sigmoidal while linear function is also sometimes used at the output layer with the view that choice between these activation functions does not make considerable differences in network's performance. In this letter, we show distinct performance between a network with linear output units and a similar network with sigmoid output units in terms of convergence behavior and generalization ability. We experimented with two types of cost functions, namely, sum-squared error used in standard Backpropagation and log-likelihood recently reported. We find that, with sum-squared error cost function and hidden units with nonsteep sigmoid function, use of linear units at the output layer instead of sigmoidal ones accelerates the convergence speed considerably while generalization ability is slightly degraded. Network with sigmoid output units trained by log-likelihood cost function yields even faster convergence and better generalization but does not converge at all with linear output units. It is also shown that a network with linear output units needs more hidden units for convergence.

A least squares approximation method of recursive digital filters for finite interval response with zero value outside the interval is presented. According to the characteristic of the method, the modified Gauss Method is utilized in iteratively determining design parameters. Convergence, together with the stability of the resulting filter, are guaranteed.

In this paper, we discuss to the intermedia synchronization problems for high speed multimedia communication. Especially, we described how software synchronization can be operated, and estimated the skew bound in CNV when considering the network delay. And we applied CNV to the intermedia synchronization and a hybrid model (HSM) is proposed. Furthermore, we used the statistical approach to evaluate the performance of the synchronization mechanisms. The results of performance evaluation show that HSM has good performance in the probability of estimation error.