The method solving Bessel's differential equation for calculating numerical values of the Bessel function Jν(x) is not usually used, but it is made clear here that the differential equation method can give very precise numerical values of Jν(x), and is very effective if we do not mind computing time. Here we improved the differential equation method by using a new transformation of Jν(x). This letter also shows a method of evaluating the errors of Jν(x) calculated by this method. The recurrence method is used for calculating the Bessel function Jν(x) numerically. The convergence of the solutions in this method, however, is not yet examined for all of the values of the complex ν and the real x. By using the differential equation method, this letter will numerically ascertain the convergence of the solutions and the precision of Jν(x) calculated by the recurrence method.

The dynamics is investigated on the delayed regulation model under period-2 perturbation described as x(t+1)={A+(-1)te}x(t){1-x(t-1)}, t=1, 2, 3 . . . The e-dependences of the bifurcation points are analyzed through usual stability analysis of fixed point and periodic solution, however one of them is derived through the stability analysis of the "virtual" period-2 solution.

In this paper, we focus on regularity and set-valued functions. Regularity was first introduced by S. C. Kleene in the propositional operations of his ternary logic. Then, M. Mukaidono investigated some properties of ternary functions, which can be represented by regular operations. He called such ternary functions "regular ternary logic functions". Regular ternary logic functions are useful for representing and analyzing ambiguities such as transient states or initial states in binary logic circuits that Boolean functions cannot cope with. Furthermore, they are also applied to studies of fail-safe systems for binary logic circuits. In this paper, we will discuss an extension of regular ternary logic functions into r-valued set-valued functions, which are defined as mappings on a set of nonempty subsets of the r-valued set {0, 1, . . . , r-1}. First, the paper will show a method by which operations on the r-valued set {0, 1, . . . , r-1} can be expanded into operations on the set of nonempty subsets of {0, 1, . . . , r-1}. These operations will be called regular since this method is identical with the way that Kleene expanded operations of binary logic into his ternary logic. Finally, explicit expressions of set-valued functions monotonic in subset will be presented.

Recently, the quantum information theory attracts much attention. In quantum information theory, the existence of superadditivity in capacity of a quantum channel was foreseen conventionally. So far, some examples of codes which show the superadditivity in capacity have been clarified. However in present stage, characteristics of superadditivity are not still clear up enough. The reason is as follows. All examples were shown by calculating the mutual information by quantum combined measurement, so that one had to solve the eigenvalue and the eigenvector problems. In this paper, we construct a simplification algorithm to calculate the mutual information by using square-root measurement as decoding process of quantum combined measurement. The eigenvalue and the eigenvector problems are avoided in the algorithm by using group covariancy of binary linear codes. Moreover, we derive the analytical solution of the mutual information for parity check codes with any length as an example of applying the simplification algorithm.

Some novel learning strategies based on set covering in Hamming geometrical space are presented and proved, which are related to the three-layer Boolean neural network (BNN) for implementing an arbitrary Boolean function with low-complexity. Each hidden neuron memorizes a set of learning patterns, then the output layer combines these hidden neurons for explicit output as a Boolean function. The network structure is simple, reliable and can be easily implemented by hardware.

This paper presents an improved method of speaker verification using the sequential probability ratio test (SPRT), which can treat the correlation between successive feature vectors. The hidden Markov model with the mean field approximation enables us to consider the correlation in the SPRT, i. e. , using the mean field of previous state, probability computation can be carried out as if input samples were independent each other.

Tail-biting trellises of linear and nonlinear block codes are addressed. We refine the information-theoretic approach of a previous work on conventional trellis representation, and show that the same ideas carry over to tail-biting trellises. We present lower bounds on the state and branch complexity profiles of these representations. These bounds are expressed in terms of mutual information between different portions of the code, and they introduce the notions of superstates and superbranches. For linear block codes, our bounds imply that the total number of superstates, and respectively superbranches, of a tail-biting trellis of the code cannot be smaller than the total number of states, and respectively branches, of the corresponding minimal conventional trellis, though the total number of states and branches of a tail-biting trellis is usually smaller than that of the conventional trellis. We also develop some improved lower bounds on the state complexity of a tail-biting trellis for two classes of codes: the first-order Reed-Muller codes and cyclic codes. We show that the superstates and superbranches determine the Viterbi decoding complexity of a tail-biting trellis. Thus, the computational complexity of the maximum-likelihood decoding of linear block codes on a tail-biting trellis, using the Viterbi algorithm, is not smaller than that of the conventional trellis of the code. However, tail-biting trellises are beneficial for suboptimal and iterative decoding techniques.

The subliminal channel is one of the methods for hiding a message in other messages. Simmons has shown conjectures on the upper bound to the bandwidth of a subliminal channel. This paper proposes a new broad-band subliminal channel embedded in the ESIGN. The bandwidth of the proposed subliminal channel is wider than that of the previous one, and it exceeds the upper bound that Simmons has conjectured. Namely, we disprove the conjectures due to Simmons. We also show that it is possible to construct the subliminal channel even if the transmitter and the subliminal receiver do not have any key in common.

The recording of electrocardiogram (ECG) signals for the purpose of finding arrhythmias takes 24 hours. Generally speaking, changes in R-R intervals are used to detect arrhythmias. Our purpose is to develop an algorithm which efficiently detects R-R intervals. This system uses the R-wave position to calculate R-R intervals and then detects any arrhythmias. The algorithm searches for only the short time duration estimated from the most recent R-wave position in order to detect the next R-wave efficiently. We call this duration a WINDOW. A WINDOW is decided according to a proposed search algorithm so that the next R-wave can be expected in the WINDOW. In a case in which an S-wave is enhanced for some reason such as the manner in which the electrodes are installed in the system, the S-wave positions are taken to calculate the peak intervals instead of the R-wave. However, baseline wander and noise contained in the ECG signal have a deterrent effect on the accuracy with which the R-wave or the S-wave position is determined. In order to improve detection, the ECG signal is preprocessed using a Band-Pass Filter (BPF) which is composed of simple Cascaded Integrator Comb (CIC) filters. The American Heart Association (AHA) database was used in the simulation with the proposed algorithm. Accurate detection of the R-wave position was achieved in 99% of cases and efficient extraction of R-R intervals was possible.

In this paper, we present simulation algorithms among enhanced mesh models. The enhanced mesh models here include reconfigurable mesh and mesh with multiple broadcasting. A reconfigurable mesh (RM) is a processor array that consists of processors arranged to a 2-dimensional grid with a reconfigurable bus system. The bus system can be used to dynamically obtain various interconnection patterns among the processors during the execution of programs. A horizontal-vertical RM (HV-RM) is obtained from the general RM model, by restricting the network topology it can take to the ones in which each bus segment must be along row or column. A mesh with multiple broadcasting (MWMB) is an enhanced mesh, which has additional broadcasting buses endowed to every row and column. We present two algorithms:1) an algorithm that simulates a HV-RM of size nn time-optimally in θ(n) time on a MWMB of size nn, and 2) an algorithm that simulates a RM of size nn in θ(log2 n) time on a HV-RM of size nn. Both algorithms use a constant number of storage in each processor. Furthermore, we show that a RM of size nn can be simulated in θ((n/m)2 log n log m) time on a HV-RM of size mm, in θ ((n/m)2 m log n log m) time on a MWMB of size mm (m < n). These simulations use θ((n/m)2) storage in each processor, which is optimal.

With the knowledge of the syndromes Sa,b, 0a,b q-2, the exact error values cannot be determined by using the conventional (q-1)2-point discrete Fourier transform in the decoding of a plane algebraic-geometric code over GF(q). In this letter, the inverse q-point 1-dimensional and q2-point 2-dimensional affine Fourier transform over GF(q) are presented to be used to retrieve the actual error values, but it requires much computation efforts. For saving computation complexity, a modification of the affine Fourier transform is derived by using the property of the rational points of the plane Hermitian curve. The modified transform, which has almost the same computation complexity of the conventional discrete Fourier transform, requires the knowledge of syndromes Sa,b, 0 a,b q-2, and three more extended syndromes Sq-1,q-1, S0,q-1, Sq-1,0.

In this paper, the use of optimal Karhunen-Loeve (KL) transform for quantization of speech line spectrum frequency (LSF) coefficients is studied. Both scalar quantizer (SQ) and vector quantizer (VQ) schemes are developed to encode efficiently the transform parameters after operating one or two-dimensional KL transform. Furthermore, the SQ schemes are also combined with entropy coding by using Huffman variable length coding (VLC). The basic idea in developing these schemes is utilizing the strong correlation of LSF parameters to reduce the bit rate for a given level of fidelity. Since the use of global statistics for generating the coding scheme may not be appropriate, we propose several adaptive KL transform systems (AKL) to encode the LSF parameters. The performance of all systems for different bit rates is investigated and adequate comparisons are made. It is shown that the proposed KL transform coding systems introduce as good as or better performance for both SQ and VQ in the examined bit rates compared to other methods in the field of LSF coding.

In the visual secret sharing scheme proposed by Naor and Shamir, a secret image is encoded into shares, of which size is larger than that of the secret image and the shares are decoded by stacking them without performing any cryptographic computation. In this paper we propose a (k,n) visual secret sharing scheme to encode a black-and-white image into the same size shares as the secret image, where the reconstructed image of the proposed scheme is visible as well as that of the conventional scheme.

This paper reports on the development of an eyeglass-type infrared-controlled telephone communication interface for the disabled. This system is comprised of four major components: A) a headset; B) an infrared transmitting module; C) an infrared receiving/signal-processing module; and D) a main controller, the Intel-8951 microprocessor. The headset with a tongue-touch panel, a wireless earphone, and a wireless microphone. The infrared transmitting module utilizes a tongue touch panel via tongue-touch circuitry which is converted to an infrared beam and a low power laser (<0.1 mW) beam. The infrared receiving/signal-processing module, receives the infrared beam and fine tunes the unstable infrared beam into standard pulses which are used as control signals. The main controller is responsible for detecting the input signals from the infrared receiving/signal-processing module and verifying these signals with the mapping table in its memory. After the signal is verified, it is released to control the keys of the telephone interface. This design concept was mainly based on the idea that the use of an infrared remote module fastened to the eyeglasses could allow the convenient control of the dialing motion on the keys of a telephone's dialing-pad which are all modified with infrared receiving/signal-processing modules. The disabled are competent for some of work, such as a telephone operator. The increase of opportunity to do a job for the disabled would help them live independently.

In the present paper we shall examine the real-time restoration of biomedical signals under additive noises. Biomedical signals measured by instruments such as catheter manometers, ambulatory electrocardiographs and thermo-dilution sensors are susceptible to distortion and noise. Therefore, such signals must be restored to their original states. In the present study, nonstationary biomedical signals are observed and described using a mathematical model, and several restoration filters that are composed of a series of applications of this model are proposed. These filters restored band-limited approximations of the original signals in real-time. In addition, redundancy is introduced into these restoration filters in order to suppress additive noise. Finally, an optimum filter that accounts for restoration error and additive noise is proposed.

In pattern recognition using neural networks, it is very difficult for researchers or users to design optimal neural network architecture for a specific task. It is possible for any kinds of neural network architectures to obtain a certain measure of recognition ratio. It is, however, difficult to get an optimal neural network architecture for a specific task analytically in the recognition ratio and effectiveness of training. In this paper, an evolutional method of training and designing feedforward neural networks is proposed. In the proposed method, a neural network is defined as one individual and neural networks whose architectures are same as one species. These networks are evaluated by normalized M. S. E. (Mean Square Error) which presents a performance of a network for training patterns. Then, their architectures evolve according to an evolution rule proposed here. Architectures of neural networks, in other words, species, are evaluated by another measurement of criteria compared with the criteria of individuals. The criteria assess the most superior individual in the species and the speed of evolution of the species. The species are increased or decreased in population size according to the criteria. The evolution rule generates a little bit different architectures of neural network from superior species. The proposed method, therefore, can generate variety of architectures of neural networks. The designing and training neural networks which performs simple 3 3 and 4 4 pixels which include vertical, horizontal and oblique lines classifications and Handwritten KATAKANA recognitions are presented. The efficiency of proposed method is also discussed.

In order to improve the efficiency of the feature extraction of backpropagation (BP) learning in layered neural networks, model switching for changing the function model without altering the map is proposed. Model switching involves map preserving reduction of units by channel fusion, or addition of units by channel installation. For reducing the model size by channel fusion, two criteria for detection of the redundant channels are addressed, and the local link weight compensations for map preservation are formulated. The upper limits of the discrepancies between the maps of the switched models are derived for use as the unified criterion in selecting the switching model candidate. In the experiments, model switching is used during the BP training of a layered network model for image texture classification, to aid its inefficiency of feature extraction. The results showed that fusion and re-installation of redundant channels, weight compensations on channel fusion for map preservation, and the use of the unified criterion for model selection are all effective for improved generalization ability and quick learning. Further, the possibility of using model switching for concurrent optimization of the model and the map will be discussed.

Dynamical theory of cellular automata on groups is developed. Main results are non-Euclidean extensions of Sato and Honda's results on the dynamics of Euclidean cellular automata. The notion of the period of a configuration is redefined in a more group theoretical way. The notion of a co-finite configuration substitutes the notion of a periodic configuration, where the new term is given to it to reflect and emphasize the importance of finiteness involved. With these extended or substituted notions, the relations among period preservablity, injectivity, and Poisson stability of parallel maps are established. Residually finite groups are shown to give a nice topological property that co-finite configurations are dense in the configuration space.

To realize S-band mobile satellite communications and broadcasting systems, the onboard mission system and equipment were designed for the Japanese Engineering Test Satellite VIII. The system performs voice communications using handheld terminals, high-speed data communications, and multimedia broadcasting through a geostationary satellite. To enhance system efficiency and flexibility, the onboard mission system features phased-array-fed reflector antennas with large antenna diameter and baseband switching through onboard processors. Configurations and performance of the subsystems and key onboard equipment, large deployable reflectors, feed arrays, beam forming networks and onboard processors, are presented. The S-band mobile systems and onboard equipment will be verified through in-orbit experiments scheduled for 2002.

Recently, optical loss increases have appeared at high temperatures in some of the optical drop cables, introduced for FTTH field experiments. Optical drop cable is installed from homes to aerial facilities, and consists of an optical fiber cable part and a self-supporting wire part. Fiber micro-bending is caused by cable sheath buckling in high temperature environments when the cable is bent with the cable part inside. Moreover, adhesion between the steel reinforcing wires and the cable sheath is effective in preventing this fiber micro-bending, which induces loss increases. This paper also shows the most suitable range of adhesive ability in terms of both practical construction and environment.