Moving-picture transmission through narrow band and high bit error rate communication channels, such as a mobile communication channel, requires improved compression rate and enhanced error resilience. Variable-length codes are one of the essential techniques of compressing digital video information. This technique is used in various video coding schemes although a bit error in the channel impairs the synchronization of variable-length codewords, resulting in propagation of the error. With a hybrid video coding method in particular, which combines motion-compensation and transform coding, once an error is detected in the coded data, subsequent data cannot be decoded. Consequently, even an error-free portion of any data received must be discarded. To minimize the influence of an error in a channel on coded video data, this paper proposes a new video coding syntax which makes the best use of the self synchronizing characteristic of variable-length Huffman codes. Owing to the Huffman code's characteristic, the proposed coding syntax enables a decoder to decode the data portion that cannot be decoded, due to an error, by the conventional syntax without adding any redundancy. Computer simulation has verified the effectiveness of this proposed syntax in video coding with a very low bitrate and erroneous communication channel.

This paper presents a new Frequency Shift Keying (FSK) demodulation method using the Short Time-Discrete Fourier Transform (ST-DFT) analysis to combat large frequency offset with time variation in low earth orbit (LEO) satellite communications systems. This demodulation method can demodulate the received signal only by searching for the instantaneous spectrum energy peaks without complicated carrier recovery. In addition, it is insensitive to the signal-to-noise ratio (SNR) degradation caused by the excessively wide bandwidth of the receiver front-end band pass filter. Furthermore, the ST-DFT analysis combined with a differential encoding scheme gives FSK demodulation method a potential robustness against large and fast time-varying frequency offset.

The two variational principles, the Maupertuis' and the Hamilton's principle, are discussed in conjunction with the Fermat's principle. These two principles are shown to describe two different aspects of waves, thus resulting in the different geometry of wave propagation, the treatment of which is thus called the stationary optics or the dynamical optics, respectively. Comparisons for the results obtained from these geometrical optics are given. Another new variational principle valid for the dynamical waves reflected/refracted at the inter-faces, which has not yet been discovered so far, is also derived.

A piece of information on the polarization effects on the effective dielectric constant εeff of a medium whose dielectric circular cylinders are randomly distributed is obtained by analyzing εeff for both E-wave and H-wave incidences. Our numerical analysis shows clearly the difference of εeff between E-wave and H-wave incidences and also shows the difference of εeff between our method and the Foldy's approximation.

In this paper, we present an analysis of microstrip line with a trapezoidal dielectric ridge in multilayered media. The method employed in this characterization is called partial-boundary element method (p-BEM) which provides an efficient technique to the analysis of the structures with multilayered media. To improve the convergence of the Green's function used in the analysis with the P-BEM, we employ a technique based on a combination of the Fourier series expansion and the method of images. Treatment on convergence for the boundary integrals is also described. After this treatment, it requires typically one tenth or one hundredth of Fourier terms to obtain the same accuracy compared with the original Green's function. Numerical results are presented for two microstrip lines that have a trapezoidal dielectric ridge placed on a one-layered substrate and a two-layered substrate. These numerical results demonstrate the effects on the characteristics of the microstrip line due to the existence of the dielectric ridge as well as the second layer between the ridge and the fundamental substrate.

The performance improvement of the partial response maximum-likelihood (PRML) system for (1, 7) run-length limited (RLL) code is studied. As a new PRML system, PR (1, 1, 0, 1, 1) system called modified E2PR4 (ME2PR4 ) followed by Viterbi detector for (1, 7) RLL code is proposed. At first, a determination method of the tap weights in transversal filter to equalize to PR (1, 1, 0, 1, 1) characteristic taking account of a noise correlation is described. And the equalization characteristics of the transversal filter are evaluated. Then, a Viterbi detector for ME2PR4 utilizing the constraint of run-length of (1, 7) RLL code is presented. Finally, the bit-error rate is obtained by computer simulation and the performance is compared with that of the conventional PRML systems called PR4, EPR4 and E2PR4 systems with Viterbi detector. The results show that among these systems our system exhibits the best performance and the SNR improvement increases with the increase in the linear density.

This paper describes some dynamical properties of higher order neural networks with decreasing energy functions. First, we will show that for any symmetric higher order neural network which permits only one element to transit at each step, there are only periodic sequences with the length 1. Further, it will be shown that for any higher order neural network, with decreasing energy functions, which permits all elements to transit at each step, there does not exist any periodic sequence with the length being over k + 1, where k is the order of the network. Lastly, we will give a characterization for higher order neural networks, with the order 2 and a decreasing energy function each, which permit plural elements to transit at each step and have periodic sequences only with the lengh 1.

This letter demonstrates that, under certain condition, the harmonic content of a rectangular pulse train is reduced by a considerable extent in the presence of another equal frequency pulse train of opposite polarity. The condition for maximum harmonic rejection is derived. It is also shown that this technique can, very effectively, be applied to reduce the harmonic content of a sequential phase detector (PD) output. This letter also presents the experimental performance of a sequential PD, incorporating this technique, in a single-loop synthesizer.

In order to improve the sensitivity of micromachined sensors applied with electrostatic fields and increase their actuated force of electrostatic micromachined actuators, "electrets," which are dielectrics carrying non equilibrium permanent space charges of polarization distribution, are very important. In this paper, positively corona charged silicon dioxide electrets, which are deposited by Plasma Chemical Vapor Deposition (PCVD) and thermally oxidized, are investigated. Physical studies will be described, in which the charge stability is correlated to Thermally Stimulated Current (TSC) measurements and to Electron Spin Resonance (ESR) analysis. Some intrinsic differences have been observed between materials. The electrets with superior long-term charge stability contain 10,000 times as much E' center (Si3 as the ones with inferior long-term charge stability. Finally, some investigations on the long-term charge storage mechanism of the positively charged silicon dioxide electret will be described.

In this paper, we report the simulation studies on MSW solitons based on numerical solution of nonlinear schrodinger equation by Split Step Fourier Transform method. We have studied both magnetostatic forward volume and surface modes that satisfy opposite nonlinear conditions. The parameters used for the simulation are obtained from experiments on nonlinear characteristics of both the modes. Important soliton properties such as nonlinear power dependence, pulse shaping, formation of multisolitons are studied and compared qualitatively with the experiments.

An approach to design for testability using register-transfer level (RTL) partial scan selection is described. We define an RTL circuit model which enables efficient description in an electronic system design automation (ESDA) tool and testability analysis which leads to effective partial scan selection for RTL design including data path circuits and control circuits such as state machines. We also introduced a method of partial scan selection at RTL which selects critical registers and state machines based on RTL testability analysis. DFT techniques using gate level testability measures have been studied and concluded that they are not successful in achieving high fault coverage [15]. However, we started this work for the following reasons, 1) In sequential ATPG procedure, more than two memory elements belonging to a functional units such as registers and state machines are often required to be justified at a time. At RTL, state machines and registers are explicitly described and recognized as functional units while gate level memory elements are scattered over the circuit. 2) As discussed in [6], if the circuit is modified so that the test sequence which causes state transition between initial and final states of sequential ATPG can be easily obtained, ATPG results can be also improved. Complex state machines can be identified at RTL. According to the experimental results, our gate level DFT achieves high fault coverage comparable with the previously published most successful DFT methods, and DFT at RTL resulted in higher fault coverage than gate level DFT at much shorter CPU time.

Hybrid image coding method is one of the most promising methods for efficient coding of moving images. The method makes use of jointly motion-compensated prediction and orthogonal transform like DCT. This type of coding scheme was adopted in several world standards such as H.261 and MPEG in ITU-T and ISO as a basic framework [1], [2]. Most of the work done in motion-compensated prediction has been based on a block matching method. However, when input moving images include complicated motion like rotation or enlargement, it often causes block distortion in decoded images, especially in the case of very low bit-rate image coding. Recently, as one way of solving this problem, some motion-compensated prediction methods based on an affine transform or bilinear transform were developed [3]-[8]. These methods, however, cannot always express the appearance of the motion in the image plane, which is projected plane form 3-D space to a 2-D plane, since the perspective transform is usually assumed. Also, a motion-compensation method using a perspective transform was discussed in Ref, [6]. Since the motion detection method is defined as an extension of the block matching method, it can not always detect motion parameters accurately when compared to gradient-based motion detection. In this paper, we propose a new motion-compensated prediction method for coding of moving images, especially for very low bit-rate image coding such as less than 64 kbit/s. The proposed method is based on a perspective transform and the constraint principle for the temporal and spatial gradients of pixel value, and complicated motion in the image plane including rotation and enlargement based on camera zooming can also be detected theoretically in addition to translational motion. A computer simulation was performed using moving test images, and the resulting predicted images were compared with conventional methods such as the block matching method using the criteria of SNR and entropy. The results showed that SNR and entropy of the proposed method are better than those of conventional methods. Also, the proposed method was applied to very low bit-rate image coding at 16 kbit/s, and was compared with a conventional method, H.261. The resulting SNR and decoded images in the proposed method were better than those of H.261. We conclude that the proposed method is effective as a motion-compensated prediction method.

In the paper a new type of Multilayer Perceptron, developed in Quaternion Algebra, is adopted to realize short-time prediction of chaotic time series. The new introduced neural structure, based on MLP and developed in the hypercomplex quaternion algebra (HMLP) allows accurate results with a decreased network complexity with respect to the real MLP. The short term prediction of various chaotic circuits and systems has been performed, with particular emphasys to the Chua's circuit, the Saito's circuit with hyperchaotic behaviour and the Lorenz system. The accuracy of the prediction is evaluated through a correlation index between the actual predicted terms of the time series. A comparison of the performance obtained with both the real MLP and the hypercomplex one is also reported.

This paper proposes linear predictive transmission diversity for TDMA/TDD personal communication systems and evaluates the effects of fading correlation and unequal average signal power Rayleigh fading on these system. The average bit error rate (BER) performance is calculated by computer simulation and the BER of zero order prediction is theoretically analyzed. The performance degradation caused by the error from prediction, fading correlation, and unequal average signal power is found to be almost independent of each other.

Conventional learning algorithms are considered to be a sort of estimation of the true recognition function from sample patterns. Such an estimation requires a good assumption on a prior distribution underlying behind learning data. On the other hand the human being sounds to be able to acquire a better result from an extremely small number of samples. This forces us to think that the human being might use a suitable prior (called presupposition here), which is an essential key to make recognition machines highly flexible. In the present paper we propose a framework for guessing the learner's presupposition used in his learning process based on his learning result. First it is pointed out that such a guess requires to assume what kind of estimation method the learner uses and that the problem of guessing the presupposition becomes in general ill-defined. With these in mind, the framework is given under the assumption that the learner utilizes the Bayesian estimation method, and a method how to determine the presupposition is demonstrated under two examples of constraints to both of a family of presuppositions and a set of recognition functions. Finally a simple example of learning with a presupposition is demonstrated to show that the guessed presupposition guarantees a better fitting to the samples and prevents a learning machine from falling into over learning.

It is shown that five optimal and one quasioptimal binary codes with respect to the Griesmer bound can be obtained from cyclic codes over GF(2fm). An [m(2em - 1), em, 2em-1m] code, a [3(22e - 1), 2e, 322e-1] code, a [2(22e - 1), 2, (22e+2 - 4)/3] code, a [3(22e - 1), 2, 22e+1 - 2] code, and a [3(22e - 1), 2(e+1), 322e-1 - 2] code are optimal and a [2(22e - 1), 2(e + 1), 22e - 2] code is quasi-optimal.

The capability of generalization is the most desirable property of a learning system. It is well known that to achieve good generalization, the complexity of the system should match the intrinsic complexity of the problem to be learned. In this work, introduction of fractal connection structure in nonlinear learning systems like multilayer perceptrons as a means of improving its generalization capability in classification problems has been investigated via simulation on sonar data set in underwater target classification problem. It has been found that fractally connected net has better generalization capability compared to the fully connected net and a randomly connected net of same average connectivity for proper choice of fractal dimension which controlls the average connectivity of the net.

From a GF(q) sequence {ai}i0 with period qn - 1 we can obtain new periodic sequences {ai}i0 with period qn by inserting one symbol b GF(q) at the end of each period. Let b0 = Σqn-2 i=0 ai. It Is first shown that the linear complexity of {ai}i0, denoted as LC({ai}) satisfies LC({ai}) = qn if b -b0 and LC({ai}) qn - 1 if b = -b0 Most of known sequences are shown to satisfy the zero sum property, i.e., b0 = 0. For such sequences satisfying b0 = 0 it is shown that qn - LC({ai}) LC({ai}) qn - 1 if b = 0.

Electronic systems are progressively replacing mechanical devices or human operation for identifying people or objects in everyday-life applications. Especially, the contactless identification systems available today have several advantages, but they cannot handle easily several simultaneously present items. This paper describes a solution to this problem, based on blind source separation techniques. The effectiveness of this approach is experimentally demonstrated, especially by using a real-time DSP-based implementation of the proposed system.

The dipole-dipole interaction in the quantum mechanical treatment of the matter-radiation dynamics, is shown to give rise to split energy levels reminiscent of the nonlinear coupled spectral features as well as a self-sustained coherent modes. Wiener's theory of nonlinear random processes is applied to the second harmonic generation (SHG), leading also to coupled spectral pulling and dipping features, due to the dual noise sources in the fundamental and the harmonic polarizations. Furthermore, the nonlinear spectral features are suggested to be applied to implement quantum (qubit) gates for computation.