In this paper, an ARMA order selection method is proposed with a fuzzy reasoning method. In order to identify the reference model with the ARMA model, we need to determine its ARMA order. A less or more ARMA order, other than a suitable order causes problems such as; lack of spectral information, increasing calculation cost, etc. Therefore, ARMA order selection is significant for a high accurate ARMA model identification. The proposed method attempts to select an ARMA order of a time-varying model with the following procedures: (1) Suppose the parameters of the reference model change slowly, by introducing recursive fuzzy reasoning method, the estimated order is selected. (2) By introducing a fuzzy c-mean clustering methed, the period of the time during which the reference model is changing is detected and the forgetting factor of the recursive fuzzy reasoning method is set. Further, membership functions used in our algorithm are original, which are realized by experiments. In this paper, experiments are documented in order to validate the performance of the proposed method.

This paper proposes high-performance multiprocessor implementation for real-time one-dimensional (1-D) statespace digital filters (SSDFs). The block-state realization of SSDFs (BSRDF) is suitable for their high speed realization and gives the characteristics of high accuracy. Previously we proposed a VLSI-oriented highly parallel architecture for BSRDF. For the purpose of speeding up and reducing hardware complexity, the distributed arithmetic, of which processing time depends only on word length, is applied to this architecture. It is implemented as a 2-D SIMD processor array, and the processor consists of n homogeneous processing elements (PEs), n being filter order. The high sampling rate of one or more hundred MHz becomes possible for high filter order. Moreover, the number of I/O data per processor can be a small fixed value for any filter order, and the number of gates can also be smaller than that in the case of using multiplier. Consequently, this proposed system can be implemented easily even in the present VLSI environment.

In this paper, a new structure which is useful for the detection of multiple sinusoids is presented. The proposed structure is based on the direct form second-order IIR notch filter using simplified adaptive algorithm. It has been shown that the convergence characteristics of the proposed structure are much improved compared with the previously proposed structure. A cascaded adaptive notch filter using the proposed second-order section is also shown. It takes multiple sinusoids corrupted by white Gaussian noise and produces the individual sinusoids at each of the outputs. The results of computer simulation are shown which confirm the theoretical prediction.

It is important to obtain a low coefficient sensitivity digital filter. This paper presents a new low coefficient sensitivity network structure that consists of a second order digital filter and a feedback path. This network structure is based on the effectiveness of the feedback path in an analog system. The coefficient sensitivity of the proposed digital filter can be control with the coefficient of the feedback path. Using this property, the digital filter with the low coefficient sensitivity is obtained. To add the feedback path makes the frequency response deviate from the characteristic of the original second order digital filter, but the deviation can be compensated with the other coefficients. A nonlinear optimization technique is employed to determine the coefficients of the digital filter. The proposed method is not effective only to narrow-band low-pass but wide-band low-pass filters.

In this paper, the fundamental characteristics of tactile recognition by electrical stimulus in order to develop a vision substitution system were described. The electrical stimulus pulse or DC voltage was applied at a touch board, and a conducting band which was connected to the ground level was fastened around a root of finger. First of all, the resistance of finger by the DC voltage was measured and the equivalent circuit of a finger was estimated. It was found that the most of resistance of this mechanism was concentrated at the contact of tip of finger and its value reached to MΩ order. And this resistance widely varied by the contact condition. The resistance of finger itself was relatively low and the contact resistance of band connectoin was about 30 kΩ. Total stray capacitance was about 26-62 nF, which was calculated by our experiments. Secondly, the minimum recognition voltage to applied stimulus pulse was measured by changing frequency, duty-ratio and voltage of pulse. It was found that the most sensitive pulse was in situation of that the frequency range was within from 60 Hz to 300 Hz, the duty-ratio of 20%, and the minimum sensitive voltage was about 13V. Lastly, this electrical stimulus pulse was applied to the touch Braille board. A touch Braille board was controlled by a computer (PC8801). In this system, an input letter from keyboard is translated to Braille code data by a computer automatically, which express the letter by the 6 points for the brind. And a Braille data is output at a touch board. By touching on the contact point of the touch board, a person can recognize Braille points by electrical stimulus. It was found that the Braille recognition by electrical stimulus pulse was available as same as it could be done by raised points.

This paper describes a novel technique to realize high performance digital sequential circuits by using Hopfield neural networks. For an example of applications of neural networks to digital circuits, a novel gate circuit, full adder circuit and latch circuit using neural networks, which have the global convergence property, are proposed. Here, global convergence means that the energy function is monotonically decreasing and each circulit always operates correctly independently of the initial values. Finally the several digital sequential circuits such as shift register and asynchronous binary counter are designed.

In order to investigate the jitter characteristics of PLLs for practical applications, we have developed a computer simulation program of PLL, which can deal with arbitrary patterns both of data and jitters, as well as a conceivable nonlinearity of the circuit performance. We used a time-domain method, namely, we solved the state equation of a charge pump type PLL with a constant time step. The jitter transfer characteristics of a conventional PLL were calculated for periodic input data patterns with sinusoidal jitters. The result agreed fairly well with the corresponding experiments. And we have revealed that an ordinary PD (Phase Detector), which detects the phase difference between input and VCO signals at only rising edges, shows the folded jitter transfer characteristics at the half of the equivalent frequency of the input signal. This folded jitter characteristics increases the total jitter for long successive '1' or '0' data patterns, because of their low equivalent sampling frequency, and might increase the jitter even for the random data patterns. Based on simulation results, we devised an improved phase detector for PLL having a low jitter characteristics. And we also applied the simulation to an FDD (Frequency Difference Detector) type fast pull-in PLL which we have proposed recently, and obtained that the jitter of it was smaller than that of a conventional PLL by 25% for PRBS (pseudo random bit sequence) NRZ code.

In cellular mobile systems, an alternative approach for a Dynamic Channel Assignment problem is presented. It adaptively assigns the channels considering the cochannel interference level. The Dynamic Channel Assignment problem is modeled on the different cellular system from the conventional one. In this paper, we formulate the rearrangement problem in the Dynamic Channel Assignment and propose a novel strategy for the problem. The proposed algorithm is based on an artificial neural network as a specific dynamical system, and is successfully applied to the cellular system models. The computer simulation results show that the algorithm utilized for the rearrangement is an effective strategy to improve the traffic characteristics.

In implementing the future Personal Communication Services (PCS), providing a system allowing simultaneous access by many subscribers is of utmost importance. The study of CDMA, as a candidate for the radio access method is being promoted for this purpose. Increasing the CDMA system capacity is determined by; the selection of a spread code having an excellent correlation characteristic; the interference cancellation method and; the method for controlling the power accordance with the near-far problems. In this paper we considered the cellular system, and have analyzed the correlation characteristic by using the PN or Walsh code as the innercell spreading code and the PN or Gold code as the intercell spreading code. We have also analyzed the sysytem capacity in terms of the correlation characteristics for different combinations of these spreading codes. It has been clarified as a result that 40 subscriber channels can be accommodated per cell by using the Walsh code and PN code as the innercell and intercell codes for the forward link (the Base Station (BS) to the Personal Station (PS)) and the PN code as both the innercell and intercell codes for the reverse link (the PS to the BS).

New communication systems via chaotic modulations are experimentally, demonstrated. They contain the wellknown chaotic circuits as its basic elements--Chua's circuits and canonial Chua's circuits. The following advantage is found in our laboratory experiments: (a) Transmitted signals have broad spectra. (b) Secure communications are possible in the sense that the better parameter matching is required in order to recover the signal. (c) The circuit structure of our communication system is most simple at this stage. (d) The communication systems are easily built at a small outlay.

A pseudoinverse rule, one of major rule to determine a weight matrix for associative memory, has large capacity comparing with other determining rules. However, it is wellknown that the rule has small domains of attraction of memory vectors on account of many spurious states. In this paper, we try to improve the problem by means of subtracting a constant from all diagonal elements of a weight matrix. By this method, many spurious states disappear and eigenvectors with negative eigenvalues are introduced for the orthocomplement of the subspace spanned by memory vectors. This method can be applied to two types of networks: binary network and analog network. Some computer simulations are performed for both two models. The results of the simulations show our improvement is effective to extend error correcting ability for both networks.

Pitch frequency is a basic characteristic of human voice, and pitch extraction is one of the most important studies for speech recognition. This paper describes a simple but effective technique to obtain correct pitch frequency from candidates (pitch candidates) extracted by the short-range autocorrelation function. The correction is performed by a neural network in consideration of the time coutinuation that is realized by referring to pitch candidates at previous frames. Since the neural network is trained by the back-propagation algorithm with training data, it adapts to any speaker and obtains good correction without sensitive adjustment and tuning. The pitch extraction was performed for 3 male and 3 female announcers, and the proposed method improves the percentage of correct pitch from 58.65% to 89.19%.

This paper describes the relaxation-based algorithms with the dynamic partitioning technique for bipolar circuit analysis. In this technique, a circuit is partitioned dynamically based on the consideration of the operating region of specified bipolar devices. This technique has been used already in the waveform relaxation method. In this paper, the dynamic circuit partitioning technique is implemented in the Iterated Timing Analysis (ITA). First, the dynamic partitioning method and its validity are described. Next, the present ITA is applied to the transient simulation of several digital bipolar circuits and compared with the waveform relaxation method.

The performance of parallel combinatory spread spectrum (PC/SS) communication systems in the frequency-nonselective, slowly Rayleigh fading channel is studied. Performance is evaluated by symbol error rate using numerical computation. To overcome the performance degradation caused by fading, we also studied the effects of selection diversity and Reed-Solomon coding applied to the PC/SS system. As a result, a remarkable improvement in error rate performance is achieved with Reed-Solomon coding and diversity technique. The coding rate for the maximum coding gain is almost a half of that in the additive white gaussian noise channel.

Data of system parameters of real systems have some uncertainty and they should be given by sets (or intervals) rather than fixed values. To analyze and design systems contaning such uncertain parameters, it is required to represent and treat uncertainty in data of parameters, and to compute value sets of characteristic polynomials and transfer functions. Interval arithmetic is one of the most powerful tools to perform such subjects. In this paper, Polygon Interval Arithmetic (PIA) on the set of polygons in the complex plane is considered, and the data structure and algorithms to execute PIA efficiently is proposed. Moreover, practical examples are shown to demonstrate how PIA is useful to compute the evaluation of value sets.

This paper presents a mathematical formulation of a data path allocation and floorplanning problem using the mixed integer linear programming, and shows some experimental results. We assume that a data flow graph and the scheduled result are given in advance. The chip area and total wire length are used for the quality measures of the solution for the problem. This method is applied to some examples, and compared with the other method reported previously in the points of the solution and computation time.

This paper presents an optimal filtering algorithm using the covariance information in linear continuous distributed parameter systems. It is assumed that the signal is observed with additive white Gaussian noise. The autocovariance function of the signal, the variance of white Gaussian noise, the observed value and the observation matrix are used in the filtering algorithm. Then, the current filter has an advantage that it can be applied to the case where a partial differential equation, which generates the signal process, is unknown.

In an earlier paper, we have shown that each section of the L-section minimal trellis diagram for a linear block code consists of parallel and structurally identical (except branch labels) subgraphs without cross connections. These parallel subgraphs are called parallel components of the section. In this paper, it is shown that if the sets of path label sequences of two parallel components have a common sequence, then the parallel components have the same branch labels, and the number of parallel components with the same branch labels in each section and the detail structure of each parallel component up to its branch labels are analyzed and expressed in terms of the dimensions of specific linear codes related to the given code. As an example, the 2ⁱ-section minimal trellis diagram for a Reed-Muller code is analyzed. Complexity measures of soft-decision maximum likelihood decoding for binary linear block codes are also discussed.

Artificial Neural Networks (ANN's) that are able to learn exhibit many interesting features making them suitable to be applied in several fields such as pattern recognition, computer vision and so forth. Learning a given input-output mapping can be regarded as a problem of approximating a multivariate function. In this paper we will report a theoretical framework for approximation, based on the well known sequences of functions named approximate identities. In particular, it is proven that such sequences are able to approximate a generally continuous function to any degree of accuracy. On the basis of these theoretical results, it is shown that the proposed approximation scheme maps into a class of networks which can efficiently be implemented with analog MOS VLSI or BJT integrated circuits. To prove the validity of the proposed approach a series of results is reported.

A new efficient waveform relaxation technique based on dynamically overlapped partitioning scheme is presented. This overlapped partitioning method enables the application of waveform relaxation technique to bipolar VLSI circuits. Instead of fixed overlapping, we select the depth of overlapping dynamically based on the sensitivity criteria. By minimizing the overlapped area, we could reduce the additional computational overhead which results from overlapping the partitions. This overlapped waveform relaxation method has better convergence properties due to smaller error introduced at each step compared with standard relaxation techniques. When overlapped partitioning is used in the case of digital circuits, the waveforms obtained after first iteration are nearly accurate. Therefore, by using these waveforms as initial guess waveforms for the second iterations we can reduce Newton-Raphson iterations at each time point.

A simple technique is proposed for improving the convergence of Newton's method in the spherical algorithms, which are metheods for tracing solution curves. A numerical example is given in order to show the effectiveness of the proposed technique.