Three-dimensional (3-D) instrumentation using an image sequence is a promising instrumentation method for intelligent systems in which accurate 3-D information is required. However, real-time instrumentation is difficult since much computation time and a large memory bandwidth are required. In this paper, a 3-D instrumentation VLSI processor with a concurrent memory-access scheme is proposed. To reduce the access time, frequently used data are stored in a cache register array and are concurrently transferred to processing elements using simple interconnections to the 8-nearest neighbor registers. Based on a row and column memory access pattern, we propose a diagonally interleaved frame memory by which pixel values of a row and column are stored across memory modules. Based on the concurrent memory-access scheme, a 40 GOPS vprocessor is designed and the delay time for the instrumentation is estimated to be 42 ms for a 256256 images.

For mobile communication systems with code division multiple access (CDMA), a new modulation scheme, π/2-shift BPSK, is proposed. The performance has been evaluated in terms of relative out-of-band power, bit-error rate (BER), and spectral efficiency. As the result, it is shown that the proposed scheme has an advantage over conventional BPSK, conventional QPSK, and π/4-shift QPSK under nonlinear amplification.

Linear programming techniques are useful in many diverse applications such as: production planning, energy distribution etc. To find an optimal solution of the linear programming problem, we have to repeat computations and it takes a lot of processing time. For high speed computation of linear programming, special purpose hardware has been sought. This paper proposes a systolic array for solving linear programming problems using the revised simplex method which is a typical algorithm of linear programming. This paper also proposes a modified systolic array that can solve linear programming problems whose sizes are very large.

The pattern spectrum has been proposed to represent morphological size distribution of an image. However, the conventional pattern spectrum cannot extract approximate shape information from image objects spotted by noisy pixels since this is based only on opening. In this paper, a novel definition of the pattern spectrum, morphological multiresolution pattern spectrum (MPS), involving both opening and closing is proposed. MPS is capable of distinguishing details from approximate information of the image.

This paper proposes a nonlinear signal processing by using a three layered network which is trained with self-organized clustering and supervised learning. The network consists of three layers, i.e., self-organized layer, an evaluation layer and an output layer. Since the evaluation layer is designed as a simple perceptron network and the output layer is designed as a fixed weight linear node, the training complexity is the same as a conventional one consisting of self-organized clustering and a simple perceptron network. In other words, quite high speed training can be realized. Generally speaking, since the data range is arbitrary large in signal procession, the network shoulk cover this range and output a value as accurately as possible. However, it may be hard for only a node in the network to output these data. Instead of this mechanism, if this dynamic range is covered by using several nodes, the complexity of each node is reduced and the associated range is also limited. This results on the higher performance of the network than conventional RBFs. This paper introduces a new non-linear spectrum estimation which consists of LPC analysis and RBF network. It is shown that accuracy spectrum envelopes can be obtained since a new RBF network can estimate some nonlinearities in a speech production.

The parameter estimation problem of point spread function is one of the most challenging and important task for image restoration. A new method for the parameter estimation in the case of motion blur is presented here. It is based on the principle that the power spectrum of the motion blurred image contains periodical minima relevant directly to the motion derection and length. Though the principle is very simple and effective in certain cases, the direct use of it may lead to poor performance an the signal-to-noise ratio (SNR) gets lower. To improve the estimation accuracy, by analyzing image noise effect on the detection of the minima, we propose a method to greatly reduce spectral noise, and give the lowest allowed SNR at which the minima may still be identified reliably. We also estimate the power spectrum of the original image, which is a must for the Wiener restoration filter, from the noisy blurred image based on a noncasual autoregressive model. Once above parameters are decided, the Wiener filter is used to restore the noisy blurred image. Our method is very practical; no parameter needs to be known a priori, or to be adjusted manually to fit into various application problems. The proposed method is finally applied to systhesized and real motion blurred images to demonstrate its effectiveness.

Genetic algorithms were introduced by Holland in 1975 as a method of solving difficult optimization problems by means of simulated evolution. A major drawback of genetic algorithms is their slowness when emulated by software on conventional computers. Described is an adaptation of the original genetic algorithm that is advantageous to hardware implementation along with the architecture of a hardware framework that performs the functions of population storage, selection, crossover, mutation, fitness evaluation, and survival determination. Programming of the framework is illustrated with the set coverage problem that exhibits a 6,000 speed-up over software emulation on a 100 MHz workstation.

This paper investigates the error rate performance of parallel combinatorial spread spectrum (PC/SS) communicaion systems that use coherent and differential multiphase modulation: multiphase parallel combinatorial spread spectrum (MPC/SS) communication systems. The PC/SS systems are multicode SS systems based on orthogonal pseudo-noise (PN) sequences. Data is transmitted by delivering a combination of multiple PN sequences among a set of pre-assigned PN sequences. In the MPC/SS systems, every PN sequence on transmission is modulated by q-ary coherent or differential phase shift keying (PSK). Symbol error rate (SER) and average bit error rate (BER) in coherent and differential MPC/SS systems are investigated. The BER comparison between the MPC/SS systems and simple multicode SS systems with q-ary coherent and differential PSK is also presented. Numerical results show that the MPC/SS systems are superior to the conventional q-ary PSK systems, if they have equal spectral efficiency.

This work presents a further development of the approach to modelling thermal (i.e. carrier-velocity-fluctuation) noise in semiconductor devices proposed in papers by the present authors. The basic idea of the approach is to apply classical theory of Ito's stochastic differential equations (SDEs) and stochastic diffusion processes to describe noise in devices and circuits. This innovative combination enables to form consistent mathematical basis of the noise research and involve a great variety of results and methods of the well-known mathematical theory in device/circuit design. The above combination also makes our approach completely different, on the one hand, from standard engineering formulae which are not associated with any consistent mathematical modelling and, on the other hand, from the treatments in theoretical physics which are not aimed at device/circuit models and design. (Both these directions are discussed in more detail in Sect. 1). The present work considers the bipolar transistor compact model derived in Ref. [2] according to theory of Ito's SDEs and stochastic diffusion processes (including celebrated Kolmogorov's equations). It is shown that the compact model is transformed into the Ito SDE system. An iterative method to determine noisy currents as entries of the stationary stochastic process corresponding to the above Ito system is proposed.

Spectral transform methods have been widely studied for classification and analysis of logic functions. Spectral methods have also been used for logic synthesis, and by use of BDDs, practical-sized synthesis problems have been solved. Wavelet theory has recently attracted the attention of researchers in the signal processing field. The Haar function is used in both spectral methods and in signal processing to obtain spectral coefficients of logic functions of signals. In this paper spectral transform-based analysis of neural nets verifying signal processing and discrete function is presented. A neural net element is defined as a discrete function with multi-valued input signals and multi-valued or binary outputs. The multi-valued variable is realized as a variable (V, W) formed by a pair of a binary value and a multi-value pulse width. The multi-valued encoding is used with the multi-valued Haar function to give meanings to the wavelet coefficients from the view of Boolean algebra. A design example shows that these conceptually different concepts are closely related.

This paper presents the evaluation for personal communication systems (PCS). Two types of PCS are supposed for low and high degree of mobility. The service area with 30km radius is covered by a multiple hexagonal cells, which are micro cells and macro cells for the low mobility and high mobility planes respectively. As for a traffic distribution, uniform and exponentially tapered traffic distributions are assumed. After defining the system model, cost evaluation form along with capacity has been derived. The evaluation and discussions are made in terms of cost economy, capacity and spectrum usage in various conditions. It is shown that there exist the optimum cell radius for the prescribed subscriber numbers and the integration of two systems is desirable for the support of full mobility with cost-effectiveness and spectrum efficiency.

An advanced intelligent network (IN) provides service management along with telecommunication services, and has a two-layer architecture, i.e., a transmission layer and an intelligent layer. An advanced IN's programmability is achieved by a service-independent platform of nodes in the intelligent layer, and service-dependent software called logic programs. In contrast to telecommunication services, models for service management have not yet been established. This paper presents both execution and specification models for service management. The execution model is composed of three hierarchies that apply to various kinds of management operation. The specification model has the capability to define the details of data items. The specification language for service management is also proposed. Simulation on dynamic SQL based DBMS solved that; (1) Logic programs for service management can be made small size on the model, and (2) To provide efficient database operation, programmability must be enhanced if service management includes table with variable number of field operation.

In this paper, a systematic method which generates the micro-architecture of Application Specific Instruction Processor (ASIP) is proposed. Different from previous works, the data path and control path are generated from the instruction sequence which is generated by translating the compiled assembly code. A graphical representation method called Register Transfer Graph (RTG) is introduced to describe the micro-operations of instruction sequence. To achieve high performance, we perform micro-operation level scheduling which dynamically assigns the micro-operations of instruction sequence to the control steps. By transforming the architecture using synthesis parameters, design space is explored more extensively. Connection cost is minimized by removing the inefficient data transfer paths.

This paper presents a discrete-time multiple short-time Fourier transform (MSTFT) suitable for a time-frequency analysis and synthesis of discrete-time nonstationary signals. An overcomplete set of multiple windows in used for a frame constitution in l2 (Z) so that higher quality signal analysis and perfect reconstruction of the signal are achieved. A design method for a prototype window is given where the window can satisfy regularity condition and have a flexible, good time and frequency characteristic under constraint of the uncertainty principle. A dual frame is constructed using the prototype windows in the framework of a frame operator method. Efficient implementation structures for the MSTFT and its inverse transform appropriate for real time numerical processing is presented. Simulation results are given to illustrate the effectiveness for design of the MSTFT. The performance advantages as a new signal analysis tool are demonstrated with an experimental signal.

The defects in the cold rolled strips have textural characteristics, which are nonuniform due to its irregularities and deformities in geometrical appearance. In order to handle the textural characteristics of images with defects, this paper proposes a surface inspection method based on textural feature extraction using the wavelet transform. The wavelet transform is employed to extract local features from textural images with defects both in the frequency and in the spatial domain. To extract features effectively, an adaptive wavelet packet scheme is developed, in which the optimum number of features are produced automatically through subband coding gain. The energies for all subbands of the optimal quadtree of the adaptive wavelet packet algorithm and four entropy features in the level one LL subband, which correspond to the local features in the spatial domain, are extracted. A neural network is used to classify the defects of these features. Experiments with real image data show good training and generalization performances of the proposed method.

A 2.4 GHz band direct sequence (DS) spread spectrum (SS) radio frequency modem with a wide bandwidth of 26 MHz in half-duplex system has been newly developed using the small size (832 mm) and highly-efficient (-57 dBm) elastic type of surface acoustic wave (SAW) convolver. The size of SS modem is 905011 mm and the weight is 75 g. The power consumption of SS modem is 1.5 W and data rate is 206 kbps with 63 chips of PN code. Electrical characteristics measurements were made to evaluate the SS modem performance.

This study proposes an amplitude limiting type spread spectrum communication to be applied to extremely low power radio wave communicaion and evaluates capability of the code division multiplex. First, changes in output from the correlation device, maximum power, and in allowable noise power are compared by computer simulation for the case where the number of multiplex channels is increased. Second, possible relationship between noise intensity and error rate is measured by actual loading experiments using a device developed for trial purpose. Third, majority decision logic is proposed for the said device to realize amplitude limiting type code division multiplex easily. When the amplitude is limited, the maximum power can be controlled at about 2 dB, and channels with more than half of the number of spread sign can be used. It is revealed that, in the spread spectrum, alteration of the number of multiplex channels is made easy by application of this method.

Narrow-band ISDN services may experience nonstationary traffic conditions. Therefore, switch design should take account of these conditions. We propose new performance measures for switching systems and describe a traffic model, which is a mixture of stationary Poissonian traffic and momentarily focused traffic. On the basis of this model, performance measures are determined so as to satisfy grade of service requirements that are in effect during some short interval after the momentarily focused traffic enters the system. We also propose an overload control scheme that uses these new performance measures. Finally, we show practical and numerical examples for the performance measures and overload control scheme.

A new structure for adaptive AR spectral estimation based on multi-band decomposition of the linear prediction error is introduced and the mathematical background for the soulution of the related adaptive filtering problem is derived. The presented structure gives rise to AR spectral estimates that represent the true underlying spectrum with better fidelity than conventional LS methods by allowing an arbitrary trade-off between variance of spectral estimates and tracking ability of the estimator along the frequency spectrum. The linear prediction error is decomposed through a filter bank and components of each band are analyzed by different window lengths, allowing long windows to track slowly varying signals and short windows to observe fastly varying components. The correlation matrix of the input signal is shown to satisfy both time-update and order-update properties for rectangular windowing functions, and an RLS algorithm based on each property is presented. Adaptive forward and backward relations are used to derive a mathematical framework that serves as a basis for the design of fast RLS alogorithms. Also, computer experiments comparing the performance of conventional and the proposed multi-band methods are depicted and discussed.

This paper proposes a novel M-ary FSK demodulation scheme using the Short Time Discrete Fourier Transform (ST-DFT) analysis named Frequency Sequence Estimation (FSE) for low earth orbit (LEO) satellite-based personal multimedia communications. The FSE is a kind of the Viterbi algorithm, searching for the maximum likely frequency path using the instantaneous ST-DFT output as a metric. It is based on the fact that the discrete time-frequency representation of the received signal can be interpreted as a trellis diagram. The proposed method has the excellent transmission performance and spectral efficiency, as well as its own hardware simplicity and frequency offset insensitivity.