There are several attempts to generate chaotic binary sequences by using one-dimensional maps. From the standpoint of engineering applications, it is necessary to evaluate statistical properties of sample sequences of finite length. In this paper we attempt to evaluate the statistics of chaotic binary sequences of finite length. The large deviation theory for dynamical systems is useful for investigating this problem.

This paper investigates the behavior of one-dimensional discrete-time binary cellular neural networks with both the A- and B-templates and gives the necessary and sufficient conditions for the above network to be stable for unspecified fixed boundaries.

A quasi-periodic signal is a periodic signal with period and amplitude variations. Several physiological signals, including the electrocardiogram (ECG), can be treated as quasi-periodic. Vector quantization (VQ) is a valuable and universal tool for signal compression. However, compressing quasi-periodic signals using VQ presents several problems. First, a pre-trained codebook has little adaptation to signal variations, resulting in no quality control of reconstructed signals. Secondly, the periodicity of the signal causes data redundancy in the codebook, where many codevectors are highly correlated. These two problems are solved by the proposed codebook replenishment VQ (CRVQ) scheme based on a bar-shaped (BS) codebook structure. In the CRVQ, codevectors can be updated online according to signal variations, and the quality of reconstructed signals can be specified. With the BS codebook structure, the codebook redundancy is reduced significantly and great codebook storage space is saved; moreover variable-dimension (VD) codevectors can be used to minimize the coding bit rate subject to a distortion constraint. The theoretic rationale and implementation scheme of the VD-CRVQ is given. The ECG data from the MIT/BIH arrhythmic database are tested, and the result is substantially better than that of using other VQ compression methods.

The purpose of this study is to show the chaotic features of rhythmic joint movement. Depending on the experimental conditions, one (or both) elbow angle(s) was (were) measured by one (or two) goniometer(s). Pacing was provided for six different frequencies presented in random order. When the frequency of the pace increased, the fractal dimension and first Lyapunov exponent tended to increase. Moreover, the first Lyapunov exponent obtained positive values for all of the observed data. These results indicate that there is chaos in rhythmic joint movement and that the larger the frequency, the more chaotic the joint movement becomes.

This paper reviews the advantages of the silicon three-dimensional MMIC technology such as low loss transmission lines, high integration level, and high Q-factor on-chip inductors. Coupled to the masterslice concept, this technology also offers simple design procedure, short turn-around-time, low cost, and potential integration with LSI circuits. A K-band amplifier and an up-converter demonstrate the high frequency operation and low-power consumption benefits of the Si 3-D MMIC technology. A C-band Si-bipolar single-chip transceiver is proposed to illustrate the high integration level offered by the masterslice concept. Finally, the recent advances we achieved toward high Q-factor on-chip inductors provide the design of the S-band low noise amplifier presented in this paper.

In this paper, we analyze the performance of a bulk handoff scheme for mixed traffic in integrated voice/data wireless mobile networks in which new and handoff voice/data calls are accepted based on prioritization of handoff requests. If fewer channels than handoff calls are available in the target cell, some handoff calls are terminated without queuing. A higher priority is given to voice handoff calls than to data handoff calls. A multidimensional birth-death process model is presented to analyze the bulk handoff performance of mixed traffic. A numerical analysis of system performance is presented to evaluate the blocking probabilities of new voice and data calls, handoff failure probabilities, and the forced termination probabilities of voice/data handoff calls.

Since components faults occurring at arbitrary places (primarily on the links) affect seriously network performance and reliability, the multicomputers operating in harsh environments should be designed to guarantee normal network-missions in presence of those faults. One solution to the end is a fault-tolerant routing scheme, which enables messages to safely reach their destinations avoiding failed links when transmission of messages is blocked by certain faults. In the paper, we develop a fault-tolerant routing algorithm with deadlock freedom in an n-dimensional meshed network, and validate its efficiency and effectiveness through proper simulations. The aspects of fault-tolerance is adopted by appending partial-adaptiveness and detouring to the e-cube algorithm, while using a wormhole routing for the backbone routing method. The phenomenon of deadlock incurred due to its adaptiveness is eliminated by classifying a physical channel into a couple of virtual channels.

Existing MultiCode-CDMA MAC protocols perform only single dimensional access control either in the code or time domain. In this paper, we propose a MAC protocol, called SCTAC which can perform simultaneous code-time access control to achieve better system utilization. Also, SCTAC intends to provide service differentiation among different traffic classes. In order to simultaneously control access in both the code and time domain, SCTAC decouples the function of transmission ordering from the function of packing the scheduled transmissions in the resource space. As such, different transmission scheduling algorithms can be adopted without altering the MAC protocol. A water filling approach is used for efficient transmission packing where each of the scheduled transmissions is treated as a rectangular capsule with an arbitrary size and the resource space is viewed as a water container. In addition, SCTAC uses different request sending probabilities with an improved probability update algorithm to achieve service differentiation. Simulation results indicate that SCTAC is capable of providing different performances to different traffic classes. The results also confirm that SCTAC can achieve higher throughput compared to single dimensional access control protocols. Therefore, SCTAC is a better MAC protocol.

In this paper, a network dimensioning approach suitable to the Internet is discussed. Differently from the traditional telephone networks, it is difficult to guarantee QoS for end-users even in a statistically sense due to an essential nature of an end-to-end communication architecture in the Internet. We should therefore adopt another approach, based on the traffic measurement. In the approach, the traffic measurement is performed for monitoring the end-to-end QoS. Then, the network adaptively controls the link capacities to meet the user's QoS demands. For this purpose, the underlying network should support such a capability that the link capacities can be flexibly reused. With the WDM network as an underlying network, an example scenario for network provisioning is finally illustrated.

The smart vision chip has a large potential for application in general purpose high speed image processing systems. In order to fabricate smart vision chips including photo detector compactly, we have proposed the application of three dimensional LSI technology for smart vision chips. Three dimensional technology has great potential to realize new biologically inspired systems inspired by not only the biological function but also the biological structure. In this paper, we describe our three dimensional LSI technology for biologically inspired circuits and the design of smart vision chips.

In this paper, an attempt was made to evaluate mental workload using chaotic analysis of EEG. EEG signals registered from Fz and Cz during a mental task (mental addition) were recorded and analyzed using attractor plots, fractal dimensions, and Lyapunov exponents in order to clarify chaotic dynamics and to investigate whether mental workload can be assessed using these chaotic measures. The largest Lyapunov exponent for all experimental conditions took positive values, which indicated chaotic dynamics in the EEG signals. However, we could not evaluate mental workload using the largest Lyapunov exponent or attractor plot. The fractal dimension, on the other hand, tended to increase with the work level. We concluded that the fractal dimension might be used to evaluate a mental state, especially a mental workload induced by mental task loading.

Currently, the most popular model in data compression theory is that of stationary ergodic sources. But there do exist sequences each of which is not emitted from any stationary ergodic source but can be compressed sufficiently by a certain algorithm. We estimate the size of the set of such sequences in terms of Hausdorff dimension.

Efficient query processing in multi-dimensional indexing structures is an important issue for multimedia data applications. In this paper, we propose incremental k-nearest neighbor query (k-NNQ) and range query algorithms for R-tree based structures. The novel aspect of these algorithms is that they make use of the notion of VP filtering, a concept borrowed from the MVP-tree. The filtering notion allows for delaying of computational overhead until absolutely necessary. By so doing, we attain considerable performance benefits while paying insignificant overhead during the construction of the index structure. We implemented our algorithms and carried out experiments to demonstrate the capability and usefulness of our method. Results show that improvements range from 8% to 23% in response time for the experimental environment that we considered.

The uniform switching system is the family of non-linear n m binary arrays constrained such that all columns are from the constant weight k vectors and all rows have weights divisible by p > 0. For this system, we present a cardinality formula and an enumerative algorithm.

In this paper, we propose a mathematical model for one-dimensional finite linear cellular automata and show connections between our model and the classical one. We then demonstrate, through some examples, that our model is a useful tool for analyzing one-dimensional finite linear cellular automata. We also extend this model to the D-dimensional case and give an algebraic characterization for it.

The maximum likelihood estimate of a mixture model is usually found by using the EM algorithm. However, the EM algorithm suffers from a local optima problem and therefore we cannot obtain the potential performance of mixture models in practice. In the case of mixture models, local maxima often have too many components of a mixture model in one part of the space and too few in another, widely separated part of the space. To escape from such configurations we proposed a new variant of the EM algorithm in which simultaneous split and merge operations are repeatedly performed by using a new criterion for efficiently selecting the split and merge candidates. We apply the proposed algorithm to the training of Gaussian mixtures and the dimensionality reduction based on a mixture of factor analyzers using synthetic and real data and show that the proposed algorithm can markedly improve the ML estimates.

A method for determination of the location, shape, and material properties of a 3D object from measurements of the scattered field, when the object is successively illuminated by a number of incident fields is presented. This work extends the method previously developed for reconstructions of 2D permittivity and conductivity from electromagnetic measurements to the more complicated full-vector 3D electromagnetic inversion. Furthermore, a frequency hopping strategy to improve the resolution of the unknown objects when the frequency is raised, is underlined. Results of numerical experiments are presented to illustrate both strengths and weaknesses of the method.

In this article, we first discuss QoS metrics of the data networks, followed by raising the challenging problems for the next-generation Internet with high-performance and high-quality. We then discuss how the WDM technology can be incorporated for resolving those problems. Several research issues for the IP over WDM networks are also identified.

This paper reports the implementation in three dimensions (3D) of diffusion models for low dose implanted dopants in silicon and the various numerical issues associated with it. In order to allow the end-users to choose between high accuracy or small calculation time, a conventional and 5-species diffusion models have been implemented in the 3D module DIFOX-3D belonging to the PROMPT plateform. By comparison with one and two-dimensional (1D and 2D) simulations performed with IMPACT-4, where calibrated models exist, the validity of this 3D models have been checked. Finally, the results obtained for a 3-dimensional simulation of a rapid thermal annealing step involved in the manufacturing of a MOS transistor are presented what show the capability of this module to handle the optimization of real devices.

The high accuracy which is necessary for modern process simulation often requires the use of Monte-Carlo ion implantation simulation methods with the disadvantage of very long simulation times especially for three-dimensional applications. In this work a new method for an accurate and CPU time efficient three-dimensional simulation of ion implantation is suggested. The approach is based on a combination of the algorithmic capabilities of a fast analytical and the Monte-Carlo simulation method.