We consider the intrinsic randomness problem for correlated sources. Specifically, there are three correlated sources, and we want to extract two mutually independent random numbers by using two separate mappings, where each mapping converts one of the output sequences from two correlated sources into a random number. In addition, we assume that the obtained pair of random numbers is also independent of the output sequence from the third source. We first show the δ-achievable rate region where a rate pair of two mappings must satisfy in order to obtain the approximation error within δ ∈ [0,1), and the second-order achievable rate region for correlated general sources. Then, we apply our results to non-mixed and mixed independently and identically distributed (i.i.d.) correlated sources, and reveal that the second-order achievable rate region for these sources can be represented in terms of the sum of normal distributions.

The asynchronous transfer mode (ATM) provides efficient switching capability for various kinds of communication services. To guarantee the minimum quality of services in the ATM networks, the bandwidth allocation setup procedure between the network nodes and users is very important. However, most of call admission control (CAC) methods which have been proposed so far are not fully appropriate to apply to real environments in terms of the complexity of the hardware implementation or the accuracy of assumptions about the cell-arrival processes. In addition, the success of broad bandwidth applications in the future multimedia environments will largely depend on the degree to which the efficiency in communication systems can be achieved, so that establishing high-speed CAC schemes in the ATM networks is an indispensable subject. This paper proposes a new cell-loss rate estimation method for the real time CAC in ATM networks. A neural network model using the Kalman filter algorithm was employed to improve the error minimizing process for the cell-loss estimation problem. In the process of optimizing the three-layer perceptron, the average, the variance, and the 3rd central moment of the number of cell arrivals were calculated, and cell-loss rate date based on the non-parametric method were adopted for outputs of the neural network. Evaluation results concerned with the convergence using the sum of square errors of outputs were also discussed in this paper. Using this algorithm, ATM cell-loss rates can be easily derived from the average and peak of cells rates coming from users. Results for the cell-loss estimation process suggest that the proposed method will be useful for high-speed ATM CAC in multimedia traffic environments.

This paper presents a special-purpose LSI chip for inverse kinematics computation of robot manipulators. It is shown that inverse kinematic solutions of kinematically simple manipulators can be systematically described with the two-dimensional (2-D) vector rotation. The chip is fabricated with the 1.5-µm CMOS gate array. The arithmetic unit on the chip is designed using the COordinate Rotation DIgital Computer (CORDIC) algorithms, and it performs six types of operations based on the 2-D vector rotation at high speed. Pipelining is used to enhance the operating ratio of the unit to 100%. The computation time of a special purpose processor which is composed of the chip and a few memory chips is approximately 50 µs for a typical six degree-of-freedom manipulator. Moreover, the chip can be used for various types of manipulators, and the software development is very easy.

A simplified algorithm for check node processing of extended min-sum (EMS) q-ary LDPC decoders is presented in this letter. Compared with the bubble check algorithm, the so-called dynamic bubble-check (DBC) algorithm aims to further reduce the computational complexity for the elementary check node (ECN) processing. By introducing two flag vectors in ECN processing, The DBC algorithm can use the minimum number of comparisons at each step. Simulation results show that, DBC algorithm uses significantly fewer comparison operations than the bubble check algorithm, and presents no performance loss compared with standard EMS algorithm on AWGN channels.

The present paper introduces a new approach to the construction of a sequence set with a zero-correlation zone for both periodic and aperiodic correlation functions. The proposed sequences can be constructed from a pair of Hadamard matrices of orders n0 and n1. The constructed sequence set consists of n0 n1 ternary sequences, each of length n0(m+2)(n1+Δ), for a non-negative integer m and Δ ≥ 2. The zero-correlation zone of the proposed sequences is |τ| ≤ n0m+1-1, where τ is the phase shift. The proposed sequence set consists of n0 subsets, each with a member size n1. The correlation function of the sequences of a pair of different subsets, referred to as the inter-subset correlation function, has a zero-correlation zone with a width that is approximately Δ times that of the correlation function of sequences of the same subset (intra-subset correlation function). The inter-subset zero-correlation zone of the proposed sequences is |τ| ≤ Δn0m+1, where τ is the phase shift. The wide inter-subset zero-correlation enables performance improvement during application of the proposed sequence set.

Subspace representation model is an important subset of visual tracking algorithms. Compared with models performed on the original data space, subspace representation model can effectively reduce the computational complexity, and filter out high dimensional noises. However, for some complicated situations, e.g., dramatic illumination changing, large area of occlusion and abrupt object drifting, traditional subspace representation models may fail to handle the visual tracking task. In this paper, we propose a novel subspace representation algorithm for robust visual tracking by using low-rank representation with graph constraints (LRGC). Low-rank representation has been well-known for its superiority of handling corrupted samples, and graph constraint is flexible to characterize sample relationship. In this paper, we aim to exploit benefits from both low-rank representation and graph constraint, and deploy it to handle challenging visual tracking problems. Specifically, we first propose a novel graph structure to characterize the relationship of target object in different observation states. Then we learn a subspace by jointly optimizing low-rank representation and graph embedding in a unified framework. Finally, the learned subspace is embedded into a Bayesian inference framework by using the dynamical model and the observation model. Experiments on several video benchmarks demonstrate that our algorithm performs better than traditional ones, especially in dynamically changing and drifting situations.

In this paper, we consider the lossy source coding problem with delayed side information at the decoder. We assume that delay is unknown but the maximum of delay is known to the encoder and the decoder, where we allow the maximum of delay to change with the block length. In this coding problem, we show an upper bound and a lower bound of the rate-distortion (RD) function, where the RD function is the infimum of rates of codes in which the distortion between the source sequence and the reproduction sequence satisfies a certain distortion level. We also clarify that the upper bound coincides with the lower bound when maximums of delay per block length converge to a constant. Then, we give a necessary and sufficient condition in which the RD function is equal to that for the case without delay. Furthermore, we give an example of a source which does not satisfy this necessary and sufficient condition.

A current mode buck/boost DC-DC converter with automatic mode transition is presented in this paper. At heavy load, a control scheme adaptively changes operation mode between peak and valley current modes to achieve high efficiency, small output voltage ripple, and fast transient response. The switching loss is reduced by operating in pure modes, and the conduction loss is reduced by decreasing the average inductor current in transition modes. At light load, the equivalent switching frequency is decreased to reduce the switching loss. An automatic mode transition between heavy load PWM mode and light load PFM mode is achieved by introducing an average load current sensing method. The converter has been implemented with a standard 0.5,$mu$m CMOS process. The output voltage ripple is less than 10,mV in all modes, and the peak efficiency is 95%.

This paper describes an analysis of the effects of electric field on nerve cells by using the Hodgkin-Huxley model. When evaluating our model, which combines an additional ionic current source and generated membrane potential, we derive the peak-to-peak value, the accumulated square of variation, and Kolmogorov-Sinai (KS) entropy of the cell-membrane potential excited by 10, 100, 1 k, and 10 kHz-sinusoidal electric fields. In addition, to obtain a comprehensive view of the time-variation patterns of our model, we used a self-organizing map, which provides a way to map high-dimensional data onto a low-dimensional domain. Simulation results confirmed that lower-frequency electric fields tended to increase fluctuations of the cell-membrane potential, and the additional ionic current source was a more dominant factor for fluctuations of the cell-membrane potential. On the basis of our model, we visually confirmed that the obtained data could be projected onto the map in accordance with responses of cell-membrane potential excited by electric fields, resulting in a combined depiction of the effects of KS entropy and other parameters.

The present paper introduces the construction of quadriphase sequences having a zero-correlation zone. For a zero-correlation zone sequence set of N sequences, each of length l, the cross-correlation function and the side lobe of the autocorrelation function of the proposed sequence set are zero for the phase shifts τ within the zero-correlation zone z, such that |τ|≤z (τ ≠ 0 for the autocorrelation function). The ratio $rac{N(z+1)}{ell}$ is theoretically limited to one. When l=N(z+1), the sequence set is called an optimal zero-correlation sequence set. The proposed zero-correlation zone sequence set can be generated from an arbitrary Hadamard matrix of order n. The length of the proposed sequence set can be extended by sequence interleaving, where m times interleaving can generate 4n sequences, each of length 2m+3n. The proposed sequence set is optimal for m=0,1 and almost optimal for m>1.

The present paper introduces a novel construction of structured ternary sequences having a zero-correlation zone (ZCZ) for both periodic and aperiodic correlation functions. The cross-correlation function and the side lobe of the auto-correlation function of the proposed sequence set are zero for phase shifts within the ZCZ. The proposed ZCZ sequence set can be generated from an arbitrary Hadamard matrix of order n. The sequence set of order 0 is identical to the r-th row of the Hadamard matrix. For m≥0, the sequence set of order (m+1) is constructed from the sequence set of order m by sequence concatenation and interleaving. The sequence set of order m has 2m subsets of size n. The length of the sequence is equal to n4m+2m+1(2m-1); The phase shift of the ZCZ for the whole sequence set is from -(2m-1) to (2m-1). The sequence set of order 0 is coincident with the rows of the given Hadamard sequence with no ZCZ. The subsets can be associated with a perfect binary tree of height m with 2m leaves. The r-th sequence subset consists of from the nr-th sequence to the ((n+1)r-1)-th sequence. The r-th subset is assigned to the r-th leaf of the perfect binary tree. For a longer distance between the corresponding leaves to the r-th and s-th sequences, the ZCZ of the r-th and s-th sequences is wider. This tree-structured width of ZCZ of a pair of the proposed sequences enables flexible design in applications of the proposed sequence set. The proposed sequence is suitable for a heterogeneous wireless network, which is one of the candidates for the fifth generation of radio access networks.