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.

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.

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.

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 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.

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 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.

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.

This paper presents a method of multiple fault diagnosis in sequential circuits by input-sequence pairs having sensitizing input pairs. We, first, introduce an input-sequence pair having sensitizing input pairs to diagnose multiple faults in a sequential circuit represented by a combinational array model. We call such input-sequence pair the sensitizing sequence pair in this paper. Next, we describe a diagnostic method for multiple faults in sequential circuits by the sensitizing sequence pair. From a relation between a sensitizing path generated by a sensitizing sequence pair and a subcircuit, the proposed method deduces the suspected faults for the subcircuits, one by one, based on the responses observed at primary outputs without probing any internal line. Experimental results show that our diagnostic method identifies fault locations within small numbers of suspected faults.

Preliminary experiments on non-destructive quantitative analysis of water vapor density in halogen lamps have been carried out. A working curve showing a relation between absorbance and water vapor density was successfully obtained by using frequency-stabilized InGaAsP/InP semiconductor laser spectrometric system.

In this paper, the bit error rate (BER) performance of the Spread Spectrum communication system with Constrained Spreading Codes (SS-CSC) is analyzed. The BER of the SS-CSC system is the same as that of the Bi-orthogonal system. Moreover, the frequency utilization efficiency of the SS-CSC system is better than that of the Bi-orthogonal system when K 10 and N = 3.

In this paper, a simple frame synchronization system for M-ary/SS communication systems is proposed, and synchronization performance and the resulting bit error rate performance are analyzed. The frame synchronization system uses racing counters and framing chips which are added to spreading sequences. M-ary/SS communication systems can improve bit error rate performance under the condition in which there is an additive white gaussian noise. Synchronization of M-ary/SS communication systems is difficult, however, because M-ary/SS communication systems have several spreading sequences. The authors proposed the simple frame synchronization system which uses only one chip in the spreading sequence as a framing signal. This system needs a long time for initial acquisition as the frame length is longer. The proposed system in this paper can make initial acquisition time short by increasing the number of framing chips. The proposed system corresponds to the conventional system when the number of framing chips is l. As the result, it is shown that several framing chips contribute to decrease the initial acquisition time. Moreover, the frame synchronization system can be applied to asynchronous M-ary/SSMA system when different framing chip pattern is assigned to each user.

In outdoor fields such as construction, mining and agriculture, there is an increasing demand for autonomous vehicles to reduce labor costs. Also, a positioning system is one key technology required for autonomous vehicle systems. For the purpose of expanding the potential of millimeter-wave applications, we have developed a positioning system in the 77-79 GHz frequency band, using the hyperbolic radio navigation method. This system operates in a restricted area with a radius of about a few hundred meters. A spread spectrum with a PN code is used as the ranging signals. We realized about 0.1 m in positioning accuracy.

In this paper, we propose a clustering based linear ordering algorithm which consists of global ordering and local ordering. In the global ordering, the algorithm forms clusters from n given vertices and orders the clusters. In the local ordering, the elements in each cluster are linearly ordered. The linear order, thus produced, is used to obtain optimal κ-way partitioning based on scaled cost objective function. When the number of cluster is one, the proposed algorithm is exactly the same as MELO [2]. But the proposed algorithm has more global partitioning information than MELO by clustering. Experiment with 11 benchmark circuits for κ-way (2 κ 10) partitioning shows that the proposed algorithm yields an average of 10.6% improvement over MELO [2] for the κ-way scaled cost partitioning.

In this paper, a new spectral subtraction technique with two microphone inputs is proposed. In conventional spectral subtraction using a single microphone, the averaged noise spectrum is subtracted from the observed short-time input spectrum. This results in reduction of mean value of noise spectrum only, the component varying around the mean value remaining intact. In the method proposed in this paper, the short-time noise spectrum excluding the speech component is estimated by introducing the blocking matrix used in the Griffiths-Jim-type adaptive beamformer with two microphone inputs, combined with the spectral compensation technique. By subtracting the estimated short-time noise spectrum from the input spectrum, not only the mean value of the noise spectrum but also the component varying around the mean value can be reduced. This method can be interpreted as a partial construction of the adaptive beamformer where only the amplitude of the short-time noise spectrum is estimated, while the adaptive beamformer is equivalent to the estimator of the complex short-time noise spectrum. By limiting the estimation to the amplitude spectrum, the proposed system achieves better performance than the adaptive beamformer in the case when the number of sound sources exceeds the number of microphones.

In this paper we propose a direct sequence spread spectrum (DS/SS) modulation method which employs Gaussian-filtered minimum shift keying (GMSK) and permits simple code acquisition. A transmitter which includes a conventional GMSK modulator and pseudo-noise (PN) code generator can achieve the proposed modulation method. The received signal can be demodulated by four-phase correlator which can obtain the correlation value of received signal even if phase difference exists between the transmitter and the receiver. The modulation method employs phase-shift-keying (PSK) by modulating the phase of transmitted PN code for data transmission. We carried out hardware experiments and the measured bit error performance ensures the validity of this modulation method. Then we designed and developed a demodulator LSI which is applicable to a modulation method such as the DS/GMSK/PSK. The LSI is suitable for demodulation of spreadspectrum signal which can be demodulated by four-phase correlator.