In this paper, we present orthogonal multi-code CDMA systems with the constant amplitude transmission. In general, the dynamic range of the amplitude of the transmitting signal is very large in the case of orthogonal multi-code CDMA systems. In order to realize the constant amplitude transmission for orthogonal multi-code CDMA systems, we propose a constant amplitude coding. First, we show the basic concept of the constant amplitude coding. And then, we show that the constant amplitude transmission can be realized by the combination of the conventional orthogonal multi-code CDMA and the constant amplitude coding. Finally, the effectiveness of the proposed method is evaluated in terms of the bit error rate performance and it is shown that the proposed method is robust to the non-linear distortion caused by a high power amplifier (HPA).

A family of nonce-based authentication and key distribution protocols based on the trusted third-party model are proposed which are not only efficient on the view points of computation and communication, but also secure against on-line and off-line password guessing attacks. A new concept of implicit or indirect challenge-response authentication which can be used to combine the processes of identify authentication and data integrity assurance during key distribution and to make the entire protocol be more concise and efficient is introduced in this paper. In the proposed family of protocols, specific protocol can be chosen such that the secure session key to be distributed is selected by specific participant in the protocol. Detailed security analyses of every protocols are given.

In this paper we develop a new family of on-line adaptive learning algorithms for blind separation of time delayed and convolved sources. The algorithms are derived for feedforward and fully connected feedback (recurrent) neural networks on basis of modified natural gradient approach. The proposed algorithms can be considered as generalization and extension of existing algorithms for instantaneous mixture of unknown source signals. Preliminary computer simulations confirm validity and high performance of the proposed algorithms.

Several types of transmission-line coupling are analyzed to use in one- and two-dimensional active antenna arrays, and a method is developed to scan the beam of the arrays using the mutual locking theory. To compensate the undesired effect of strong radiative coupling of the nearest neighbor elements on the phased array performance, addition of resistive stubs to the end elements is proposed. In a 14 array it was observed that after the connection of resistive stubs, the scanning range of the array increased considerably. The effect of oscillator amplitudes on the phased array behavior is explored numerically. In the experiments main beam of 22 and 33 active antenna arrays were steered up to 25 and 15, respectively in the H-plane.

A noise reduction filter composed of a sandglass-type neural network (Sandglass-type Neural network Noise Reduction Filter: SNNRF) was proposed in the present paper. Sandglass-type neural network (SNN) has symmetrical layer construction, and consists of the same number of units in input and output layers and less number of units in a hidden layer. It is known that SNN has the property of processing signals which is equivalent to KL expansion after learning. We applied the recursive least square (RLS) method to learning of SNNRF, so that the SNNRF became able to process on-line noise reduction. This paper showed theoretically that SNNRF behaves most optimally when the number of units in the hidden layer is equal to the rank of covariance matrix of signal component included in input signal. Computer experiments confirmed that SNNRF acquired appropriate characteristics for noise reduction from input signals, and remarkably improved the SN ratio of the signals.

In this paper, a post-layout optimization technique for power dissipation and timing of cell-based Bipolar ECL LSIs is proposed. An ECL LSI can operate at a frequency of a few GHz but the power dissipation is very high compared to CMOS LSIs, which makes the systems using ECL quite expensive. Therefore it is crucial to develop of CAD techniques that minimize the power dissipation of an ECL LSI without decreasing its performance. To begin with, power and delay models of an ECL gate are presented as functions of its switching current. The power dissipation is a linear function of the switching current and the delay time is its hyperbolic function. These functions are obtained considering the post-layout interconnect capacitance and resistance to make the optimization results accurate enough. Using the delay model, a set of timing constraints specifying the max/min cell delay and the clock skew are extracted. This set of constraints in then given to a nonlinear programming package. The objective functions are clock skew time, the clock cycle time and the power dissipation, which are optimized in this order. With the minimum delay and hold constraints, the problem is not convex so that conventional convex programming approach cannot be used. As a result of the optimization, the switching currents for cells are obtained. These are realized within cells by regulating programmable resistors", which is a special feature of our ECL cell library. Since the above optimization is carried out after the placement and routing of the circuit, it can take accurate delay and power estimation into consideration. Experimental results show more than 40% power reductions for circuits including a real communication system chip, compared to the max power versions. The clock cycle time was maintained or even made faster due to the efficient clock skew optimization.

This paper deals with on-line signature verification. A signature is obtained as a sequence of x, y-coordinates of pen-tip movement and writing pressure. The features of a signature are derived from the coordinates and the writing pressure and are decomposed into two principal features, shape and motion, using the DP-matching technique. We found that each point of a signature varies each time to some degree. However, the degrees of local variations subject to points, as some points are relatively stable and do not vary much while some of them are not. In this paper, we propose to incorporate weighted local variations based on the stability of each point so as to evaluate the difference of two signatures locally as well as globally. The dissimilarity measures are presented with respect to the corresponding features and are combined into one for efficient verification. In addition to the x, y-coordinates, the writing pressure is also considered to be part of shape. Experiments were carried out with a database which consists of 300 genuine signatures and 300 forgeries collected from 10 subjects. The effectiveness of incorporating the weighted local variation is shown by the experimental results. It contributes to an average increase in the correct verification rate as the correct verification rate increased 1.0% and was found to be 98.7%.

This paper describes an on-line Kanji character recognition method that solves the one-to-one stroke correspondence problem with both the stroke-number and stroke-order variations common in cursive Japanese handwriting. We propose two kinds of complementary algorithms: one dissolves excessive mapping and the other dissolves deficient mapping. Their joint use realizes stable optimal stroke correspondence without combinatorial explosion. Also, three kinds of inter-stroke distances are devised to deal with stroke concatenation or splitting and heavy shape distortion. These new ideas greatly improve the stroke matching ability of the selective stroke linkage method reported earlier by the authors. In experiments, only a single reference pattern for each of 2,980 Kanji character categories is generated by using training data composed of 120 patterns written carefully with the correct stroke-number and stroke-order. Recognition tests are made using the training data and two kinds of test data in the square style and in the cursive style written by 36 different people; recognition rates of 99.5%, 97.6%, and 94.1% are obtained, respectively. Moreover, comparative results obtained by the current OCR technique as applied to bitmap patterns of on-line character data are presented. Finally, future work for enhancing the stroke matching approach to cursive Kanji character recognition is discussed.

It is demonstrated with the Berlekamp-Massey shift-register synthesis algorithm that the linear complexity value of binary complementary sequences is at least 3/4 of the sequence length. For some sequence pairs the linear complexity value can be even 0.98 times the sequence length. In the light of these results strongly non-linear complementary sequences are considered suitable for information security applications employing the spread-spectrum (SS) technique.

This work deals with thermal-noise modeling for silicon vertical bipolar junction transistors (BJTs) and relevant integrated circuits (ICs) operating at low currents. The two-junction BJT compact model is consistently derived from the thermal-noise generalization of the Shockley semiconductor equations developed in work which treats thermal noise as the noise associated with carrier velocity fluctuations. This model describes BJT with the Itô non-linear stochastic-differential-equation (SDE) system and is suitable for large-signal large-fluctuation analysis. It is shown that thermal noise in silicon p-n-junction diode contributes to "microplasma" noise. The above model opens way for a consistent-modeling-based design/optimization of bipolar device noise performance with the help of theory of Itô's SDEs.

We present a framework for the unsupervised segmentation of time series. It applies to non-stationary signals originating from different dynamical systems which alternate in time, a phenomenon which appears in many natural systems. In our approach, predictors compete for data points of a given time series. We combine competition and evolutionary inertia to a learning rule. Under this learning rule the system evolves such that the predictors, which finally survive, unambiguously identify the underlying processes. The segmentation achieved by this method is very precise and transients are included, a fact, which makes our approach promising for future applications.

This paper presents a system for recognition of on-line cursive Hangul (Korean characters) by means of DP matching of structural information. The penalty function has the following special features. In order to prevent short spurious strokes from causing large penalties, an input stroke is weighted by its length relative to other input strokes. In order to make use of pen-up and pen-down information, a penalty is incurred when 2 strokes of differing type (i.e. pen-up with pen-down) are matched. Finally, to reduce the chance of obtaining a suboptimal solution which can result from using the greedy algorithm in DP matching, we look-ahead an extra match. In a computer simulation we obtained a recognition rate of 92% for partially cursive characters and 89% for fully cursive characters. Furthermore, for both cases combined the correct character appears 98% of the time in the top 10 candidates. Thus we confirmed that the proposed algorithm is effective in recognizing cursive Hangul.

In the course of the development of the "Hyper Hospital," a novel medical care system constructed in the computerized information network using virtual reality as its human interface, we devised a virtual reality world creating system which allows users to con figure the world interactively. The re-configuration of the virtual world was designed to be carried out without interruptions of activity and the world can continue to exist during the reconfiguration process. This facility comprises an important part of our Hyper Hospital system because one of our major goals of this proposal of the Hyper Hospital is to restore maximum freedom for patients in the medical care system. Discussion was given in the present study with respect to the basic requirements of the system to be realized, including discussions on the permission given to the participants of different levels, and means by which to modify the structure of the virtual world. A preliminary implementation was described following this general consideration. The developed prototype was shown to be practically suitable to the test of our virtual environment applied to realistic medical scenes.

A multi-layer perceptron (MLP) acting directly in the time-domain is applied as a speech signal enhancer, and the performance examined in the context of three common classes of degradation, namely low bit-rate CELP degradation is non-linear system degradation, additive noise, and convolution by a linear system. The investigation focuses on two topics: (i) the influence of non-linearities within the network and (ii) network topology, comparing single and multiple output structures. The objective is to examine how these characteristics influence network performance and whether this depends on the class of degradation. Experimental results show the importance of matching the enhancer to the class of degradation. In the case of the CELP coder the standard MLP with its inherently non-linear characteristics is shown to be consistently better than any equivalent linear structure (up to 3.2 dB compared with 1.6 dB SNR improvement). In contrast, when the degradation is from additive noise, a linear enhancer is always, superior.

This paper describes new modeling methods combining neural network and hidden Markov model applicable to modeling a time series such as speech signal. The idea assumes that the sequence is nonstationary and is a nonlinear autoregressive process whose parameters are controlled by a hidden Markov chain. One is the model where a non-linear predictor composed of a multi-layered neural network is defined at each state, another is the model where a multi-layered neural network is defined so that the path from the input layer to the output layer is divided into path-groups each of which corresponds to the state of the Markov chain. The latter is an extended model of the former. The parameter estimation methods for these models are shown, and other previously proposed models--one called Neural Prediction Model and another called Linear Predictive HMM--are shown to be special cases of the NPHMM proposed here. The experimental result affirms the justification of these proposed models.

When communication network planning-design is performed, especially in a short-term case, it is important to utilize existing facilities in the construction of the new network. In this paper, link capacity assignment problem (CA problem) for packet-switched networks is investigated with the consideration of the existing network. To deal with this, per-unit cost of existing link capacity is thought to be less than that of newly installed capacity and a link cost function is modeled by a non-linear, non-differentiable one which is composed of two portions of capacity cost. After formulating the CA problem, two optimum algorithms derived from Lagrange multiplier method are presented and a modified algorithm is used for solving the CA problem in order to reduce the computation time. Some numerical results show that according to the values of link traffic flows, there will be links whose capacities must be set equally to the existing values. Moreover, when link cost difference is introduced in the CA problem, the number of links that the capacities of which have to be changed from existing values is less than that of linear cost function case, i.e., the case without consideration of the cost difference in link capacity.

When we design a human interface of a computer-mediated communication (CMC) system, it is important to take a socio-behavioral approach for understanding the nature of the human communication. From this point of view, we conducted experimental observations and post-experimental questionnaires to investigate communicative characteristics in a teleconference using Fujitsu Habitat" visual telecommunication software. We experimentally held the following three kinds of small-group conferences consisting of five geographically distributed participants: (a) teleconference using a visual telecommunication system (Fujitsu Habitat"), (b) teleconference using a real-time keyboard telecommunication system of NIFTY-Serve and (c) live face to face physical conference. Analyses were made on (1) effects of the media on utterance behaviors of conference members, and (2) satisfaction of conference members with communicative functions of the media. Satisfaction was measured by a seven-level rating scale. We found that participants in a telconference held by using Habitat showed significant differences in contents of utterances and the rating of satisfaction with nine communicative functions compared with those of conferences held by using a real-time keyboard telecommunication system and a live face-to-face conference. These results suggest some features that could facilitate multi-participant on-line electronic conferences and conversations.

A technique for pulse code modulation (PCM) encoding using a T-Model neural network is described. Performance evaluation on both the T-Model and the Hopfield model neural-based PCM encoders is carried out with PSpice simulations. The PSpice simulations also show that the T-Model neural-based PCM encoder computes to a global minimum much more effectively and more quickly than the Hopfield one.

In this paper we introduce the Piecewise Linear Radial Basis Function Model (PWL-RBFM), a new nonlinear model that uses the well known RBF framework to build a PWL functional approximation by combining an l1 norm with a linear RBF function. A smooth generalization of the PWL-RBF is proposed: it is obtained by substituting the modulus function with the logistic function. These models are applied to several time series prediction tasks.

In this paper, we present Branching Oriented System Equation based on-line error correction scheme for recursive digital signal processing. The target digital signal processing is linear and time-invariant, and the algorithm includes multiplications with constant coefficient, additions and delays. The difficulties of the algorithm-level fault tolerance for such algorithm without structural regularity include error distribution problem and right timing of error correction. To escape the error distribution problem, multiple fan-out nodes in an algorithm are specified as the nodes at which error corrections are performed. The Branching Oriented Graph and Branching Oriented System Equation are so introduced to formulate on-line correction schemes based on this strategy. The Branching Oriented Graph is treated as the collection of computation sub-blocks. Applying checksum code independently to each sub-block is our most trivial on-line error correction scheme, and it results in, with appropriate selection of error identification process, TMR in sub-block level. One of the advantages of our method is in the reduction of redundant operations performed by merging some computation sub-blocks. On the other hand, the schedulability of the system is an important issue for our method since our on-line error correction mechanism induces additional data dependencies. In this paper, the schedulability condition and some modifications on the scheme are also discussed.