The uncertainty involved in the gradient constraint for optical flow detection is often modeled as constant Gaussian noise added to the time-derivative of the image intensity. In this paper, we examine this modeling closely and investigate the error behavior by experiments. Our result indicates that the error depends on both the spatial derivatives and the image motion. We propose alternative uncertainty models based on our experiments. It is shown that the optical flow computation algorithms based on them can detect more accurate optical flow than the conventional least-squares method.

One of the important properties of multihop network is the mean internodal distance to evaluate the transmission delay, and the connective semi-random network achieves smaller mean internodal distance than other networks. However, the results are shown only by computer simulation and no theoretical analysis is investigated. Moreover, the network connective probability of the connective semi-random network is relatively small. In this paper, we propose the restricted connective semi-random network whose network connective probability is larger than that of the conventional connective semi-random network. And we theoretically analyze the mean internodal distance and the network connective probability of these two networks. It is shown that if the restriction is loose, the mean internodal distance of our model is almost the same as that of the conventional model, whereas the network connective probability of our model is larger than that of the conventional model. Moreover, the theoretical analyzed results of the mean internodal distance agree well with the simulated results in the conventional model and our model with small restriction.

McEliece and Swanson offerred an upper bound on the decorder error probability of Reed-Solomon codes. In this paper, we investigate the decorder error probability of binary linear block codes and verify its properties, and apply it to binary primitive BCH codes. It is shown that the decorder error probability of an (n,k,t) binary linear block code is determined by PE uniquely if it is a constant. We derive the decorder error probability of (n,k,t) binary primitive BCH codes with n=2m-1 and +1 and show that the decorder error probabilities of those codes are close to PE if codelengh is large and coderate is high. We also compute and analyze the decorder error probabilities of some binary primitive BCH codes.

Many ATM switching modules with high performance have been proposed and analyzed. A development of a large scale ATM switching system (e.g., used as a central switch) is the key to realization of the broadband ISDN. However, the dimension of ATM switching ICs is limited by the technological and physical constraints on VLSI. A multistage switching configuration is one of the promising configurations for a large scale ATM switch. In this paper, we treat a 3-stage switching configuration with no internal bufferes; i.e., bufferless switches are employed at the first and second stages, and output buffered switches at the third stage. A short-term cell loss probability is analyzed in order to examine the influence of bursty traffic on performance of the bufferless switch used at the first two stages. Furthermore, we propose a 4-stage switching configuration with traffic distributors added at the first stage. This switch provides more paths between a pair of input and output ports than the 3-stage switching configuration mentioned above. A few schemes to distribute cells are compared. It is shown that the distributor successfully reduces the deterioration of cell loss probability due to bursty traffic by splitting incoming cells into several switching modules.

The aliasing probability was analyzed for MISRs when the error probability for each input was different. A closed form expression was derived by applying the complete weight distributions of linear codes over a Galois field and its dual codes. The aliasing probability for MISRs characterized by non-primitive polynomials was also analyzed. The inner product for binary representation of symbols was used instead of multiplication over a Galois field. The results show the perfect expression for analyzing the aliasing probability of MISRs.

This paper is concerned with the evaluation of the block error probability Pic of a block modulation code for closest coset decoding over an AWGN channel. In most cases, the conventional union bound on Pic for closest coset decoding is loose not only at low signal-to-noise ratios but at relatively high signal-to-noise ratios. In this paper, we introduce a new upper bound on the probability of union of events by using the graph theory and we derive an improved upper bound on Pic for some block modulation codes using closest coset decoding over an AWGN channel. We show that the new bound is better than the conventional union bound especially at relatively high signal-to-noise ratios.

We consider slotted ALOHA systems with a controlled output power level. The systems were proposed to improve the throughput performance by the capture effect. However widely used linear modulation systems have no capture effect, and a power level distribution dominates the performance in those systems. In this paper we consider linear modulation systems employing PSK. We introduce an average error probability of the highest power signal as a performance measure, and a uniform distribution is applied to the error probability analysis. Numerical results show the superiority of the systems with uniform distribution to a conventional slotted ALOHA in a heavy traffic condition. On the other hand, in a light traffic condition, the optimal power distribution which minimizes the error probability is obtained for 2-level ALOHA. We also propose the power level selection method to search the optimal power level. The validity of analytical results are confirmed by simulations.

The word error probability of linear block codes is computed for diversity systems with maximal ratio combining in mobile communications with three decoding algorithms: error correction (EC), error/erasure correction (EEC), and maximum likelihood (ML) soft decoding algorithm. Ideal interleaving is assumed. EEC gives 0.1-1.5dB gain over EC. The gain of EEC over EC decreases as the number of diversity channels increases. ML soft gives 1.8-5.5dB gain over EC.

One of the most effective methods in speech recognition is the HMM which has been used to model speech statistically. The discrete distribution and the continuos distribution HMMs have been widely used in various applications. However, in recent years, HMMs with various output probability functions have been proposed to further improve recognition performance, e.g. the Gaussian mixture continuous and the semi-continuous distributed HMMs. We recently have also proposed the RBF (radial basis function)-based HMM and the VQ-distortion based HMM which use a RBF function and VQ-distortion measure at each state instead of an output probability density function used by traditional HMMs. In this paper, we describe the RBF-based HMM and the VQ-distortion based HMM and compare their performance with the discrete distributed, the Gaussian mixture distributed and the semi-continuous distributed HMMs based on their speech recognition performance rates through experiments on speaker-independent spoken digit recognition. Our results confirmed that the RBF-based and VQ-distortion based HMMs are more robust and superior to traditional HMMs.

A new upper hound on the error probability for maximum likelihood sequence estimation of digital signaling on intersymbol interference channels with additive white Gaussian noise is presented. The basic idea is to exclude all parallel error sequences and to exclude some of the overlapping error events from the union bound. It is shown that the new upper bound can be easily and efficiently computed by using a properly labeled error-state diagram and a one-directional stack algorithm. Several examples are presented that compare the new upper bound with bounds previously reported in the literature.

Some CMOS gates are topologically asymmetric in inputs, even though they are logically symmetric. It implies a possibility to reduce power consumption by optimizing signal assignment to the inputs. In this study we theoretically derive power consumption of 2-input NAND gate based on transition probability of input signals, with taking into account charging current due to an internal node. We also propose a signal assignment method to input terminals for reducing power consumption reduction by extending our method for large circuits, and demonstrate the effect of power consumption reduction by the present method.

In the actual sound environmental systems, it seems to be essentially difficult to exactly evaluate a whole probability distribution form of its response fluctuation, owing to various types of natural, social and human factors. We have reported a unified probability density expression in the standard expansion form of Hermite type orthonormal series taking a well-known Gaussian probability density function (abbr. p.d.f.) as the basis for generally evaluating non-Gaussian, non-linear correlation and/or non-stationary properties of the fluctuation phenomenon. However, in the real sound environment, there still remain many actual problems on the necessity of improving the above standard type probability expression for practical use. First, a central point in this paper is focused on how to find a new probabilistic theory of practically evaluating the variety and complexity of the actual random fluctuations, especially through newly introducing an equvivalence transformation toward the standard type probability expression mentioned above in the expansion form of Hermite type orthonormal series. Then, the effectiveness of the proposed theory has been confirmed experimentally too by applying it to the actual problems on the response probability evaluation of various sound insulation systems in an acoustic room.

In this study, after focussing on an energy (or intensity) scaled variable of acoustic systems, first, a new regression analysis method is theoretically proposed by introducing a multiplicative noise model suitable to the positively scaled stocastic system. Then, the effectiveness of the proposed method is confirmed experimentally by applying it to the actual acoustic data.

The statistical properties of insertion losses and return losses for optical connectors are investigated theoretically using the probability theory and the Monte Carlo simulation. Our investigation is focused on an orientation method for reducing insertion loss by which a fiber-core center is adjusted in a region of within a certain angle to the positioning key direction. It is demonstrated that the method can significantly improve insertion losses, and that an adjusting operation angle of 90 degrees is sufficient to realize an insertion loss of less than 0.5 dB with 99% cumulative probability. Good agreement was obtained between the theoretical distribution and the experimental results for single-mode fiber connection. Consequently, it is indicated that the statistical distributions of insertion losses and return losses of optical connectors in the field can be predicted theoretically from the values measured in the factory by connection to a master connector.

A specific signal in most of actual environmental systems fluctuates complicatedly in a non-Gaussian distribution form, owing to various kinds of factors. The nonlinearity of the system makes it more difficult to evaluate the objective system from the viewpoint of internal physical mechanism. Furthermore, it is very often that the reliable observation value can be obtained only within a definite domain of fluctuating amplitude, because many of measuring equipment have their proper dynamic range and the original random wave form is unreliable at the end of amplitude fluctuation. It becomes very important to establish a new signal processing or an evaluation method applicable to such an actually complicated system even from a functional viewpoint. This paper describes a new trial for the signal processing along the same line of the extended regression analysis based on the Bayes' theorem. This method enables us to estimate the response probability property of a complicated system in an actual situation, when observation values of the output response are saturated due to the dynamic range of measuring equipment. This method utilizes the series expansion form of the Bayes' theorem, which is applicable to the non-Gaussian property of the fluctuations and various kinds of correlation information between the input and output fluctuations. The proposed method is newly derived especially by paying our attention to the statistical information of the input-output data without the saturation operation instead of that on the resultantly saturated observation, differing from the well-known regression analysis and its improvement. Then, the output probability distribution for another kind of input is predicted by using the estimated regression relationship. Finally, the effectiveness of the proposed method is experimentally confirmed too by applying it to the actual data observed for indoor and outdoor sound environments.

This paper proposes a dynamically randomized version of DES (called RDES) in which a input-dependent swapping Sk(X) is added onto the right half of the input in each round of DES. This new scheme decreases the probability of success in differential cryptanalysis because it decreases the characteristic probability. Each "best" two-round characteristic probability is analyzed for typical schemes of the RDES: (i) RDES-1 with a simple one-level swapping, (ii) RDES-1' with an optimal one-level swapping, (iii) RDES-2 with a simple two-level swapping, and (iv) RDES-2' with an optimal two-level swapping. The main results are as follows. (a) The differential attacks on the 16-round RDES-1' and the 16-round RDES-2 require more computational time than the exhaustive search. (b) A differential attack is substantially inapplicable to the 16-round RDES-2' because more than 263 chosen plaintext pairs are required. (c) The encryption/decryption speed of the n-round RDES is almost the same as that of the n-round DES.

The generation and design of a stationary Markov signal are discussed as an inverse problem, in which one looks for a transition probability when a stationary probability distribution is given. This paper presents a new solution to the inverse problem, which makes it possible to design and generate a Markov random signal with arbitrary probability distribution and an exponential correlation function. Several computer results are illustrated in figures.

The blocking probabilities of n64Kb/s multi-slot calls are generally much higher than that of single slot calls. In order to improve these blocking probabilities of multi-slot calls, we propose a scheme to limit the number of time slots to be searched for lower rate calls. We analyze the performance of our scheme in a double-buffered time-space-time switching network which accommodates multi-slot calls as well as single-slot calls. The proposed method yields the reduced blocking probabilities of multi-slot calls, the increased traffic handling capacity and the reduced CPU processing load, compared with those of the conventional methods.

The main problem in statistical pattern recognition is to design a classifier. Many researchers point out that a finite number of training samples causes the practical difficulties and constraints in designing a classifier. However, very little is known about the performance of a classifier in small training sample size situations. In this paper, we compare the classification performance of the well-known classifiers (k-NN, Parzen, Fisher's linear, Quadratic, Modified quadratic, Euclidean distance classifiers) when the number of training samples is small.

Queueing problems are investigated for very wide classes of input traffic and service time models to obtain good loss probability and waiting time probability approximation. The proposed approximation is based on the fundamental recursion formula and the Chernoff bound technique, both of which requires no particular assumption for the stochastic nature of input traffic and service time, such as renewal or markovian properties. The only essential assumption is stationarity. We see that the accuracy of the obtained approximation is confirmed by comparison with computer simulation. There are a number of advantages of the proposed method of approximation when we apply it to network capacity design or path accommodation design problems. First, the proposed method has the advantage of applying to multi-media traffic. In the ATM network, a variety of bursty or non-bursty cell traffic exist and are superposed, so some unified analysis methodology is required without depending each traffic's characteristics. Since our method assumes only the stationarity of input and service process, it is applicable to arbitrary types of cell streams. Further, this approach can be used for the unexpected future traffic models. The second advantage in application is that the proposed probability approximation requires only small amount of computational complexity. Because of the use of the Chernoff bound technique, the convolution of every traffic's probability density fnuction is replaced by the product of probability generating functions. Hence, the proposed method provides a fast algorithm for, say, the call admission control problem. Third, it has the advantage of accuracy. In this paper, we applied the approxmation to the cases of homogeneous CBR traffic, non-homogeneous CBR traffic, M/D/1, AR(1)/D/1, M/M/1 and D/M/1. In all cases, the approximating values have enough accuracy for the exact values or computer simulation results from low traffic load to high load. Moreover, in all cases of the numerical comparison, our approximations are upper bounds of the real values. This is very important for the sake of conservative network design.