In digital speech communication over noisy high packet loss rate wireless channels, improving the overall performance of the realtime speech coding and transmission system is of great importance. A novel joint speech coding and transmission algorithm is proposed by fully exploiting the correlation between speech coding, channel coding and the transmission process. The proposed algorithm requires no algorithm delay and less bandwidth expansion while greatly enhancing the error correcting performance and the reconstructed speech quality compared with conventional algorithms. Simulations show that the residual error rate is reduced by 84.36% and the MOS (Mean Opinion Score) is improved over 38.86%.

Improving the overall performance of reliable speech communication in ultrashort wave radios over very noisy channels is of great importance and practical use. An iterative joint source-channel (de-)coding and (de-)modulation (JSCCM) algorithm is proposed for ITU-T Rec.G.729EV by both exploiting the residual redundancy and passing soft information throughout the receiver while introducing a systematic global iteration process. Being fully compatible with existing transmitter structure, the proposed algorithm does not introduce additional bandwidth expansion and transmission delay. Simulations show substantial error correcting performance and synthesized speech quality improvement over conventional separate designed systems in delay and bandwidth constraint channels by using the JSCCM algorithm.

The task of joint channel and data estimation based on the maximum likelihood principle is addressed using a continuous and discrete particle swarm optimization (PSO) algorithm over additive white Gaussian noise channels. The PSO algorithm works at two levels. At the upper level continuous PSO estimates the channel while at the lower level, discrete PSO detects the data. Simulation results indicate that under the same conditions, PSO outperforms the best of the published alternatives.

A new type of humanoid robot arm which can coexist and be interactive with human beings are looked for. For the purpose of implementation of human smooth and fast movement to a pneumatic robot, the author used a humanoid robot arm with pneumatic agonist-antagonist actuators as endoskeletons which has control mechanism in the stiffness of each joint, and the controllability was experimentally discussed. Using Kitamori 's method to experimentally decide the control gains and using I-PD controller, three joints of the humanoid robot arm were experimentally controlled. The damping control algorithm was also adopted to the wrist joint, to modify the speed in accordance with the power. The results showed that the controllability to step-wise input was less than one degree in error to follow the target angles, and the time constant was less than one second. The simultaneous input of command to three joints was brought about the overshoot of about ten percent increase in error. The humanoid robot arm can generate the calligraphic motions, moving quickly at some times but slowly at other times, or particularly softly on some occasions but stiffly on other occasions at high accuracy.

We investigate the problem of joint transmitter and receiver power allocation with the minimax mean square error (MSE) criterion for uplink transmissions in a multi-carrier code division multiple access (MC-CDMA) system. The objective of power allocation is to minimize the maximum MSE among all users each of which has limited transmit power. This problem is a nonlinear optimization problem. Using the Lagrange multiplier method, we derive the Karush-Kuhn-Tucker (KKT) conditions which are necessary for a power allocation to be optimal. Numerical results indicate that, compared to the minimum total MSE criterion, the minimax MSE criterion yields a higher total MSE but provides a fairer treatment across the users. The advantages of the minimax MSE criterion are more evident when we consider the bit error rate (BER) estimates. Numerical results show that the minimax MSE criterion yields a lower maximum BER and a lower average BER. We also observe that, with the minimax MSE criterion, some users do not transmit at full power. For comparison, with the minimum total MSE criterion, all users transmit at full power. In addition, we investigate robust joint transmitter and receiver power allocation where the channel state information (CSI) is not perfect. The CSI error is assumed to be unknown but bounded by a deterministic value. This problem is formulated as a semidefinite programming (SDP) problem with bilinear matrix inequality (BMI) constraints. Numerical results show that, with imperfect CSI, the minimax MSE criterion also outperforms the minimum total MSE criterion in terms of the maximum and average BERs.

Bubble-sort graphs are variants of Cayley graphs. A bubble-sort graph is suitable as a topology for massively parallel systems because of its simple and regular structure. Therefore, in this study, we focus on n-bubble-sort graphs and propose an algorithm to obtain n-1 disjoint paths between two arbitrary nodes in time bounded by a polynomial in n, the degree of the graph plus one. We estimate the time complexity of the algorithm and the sum of the path lengths after proving the correctness of the algorithm. In addition, we report the results of computer experiments evaluating the average performance of the algorithm.

Functional Electrical Stimulation (FES) can be effective in assisting or restoring paralyzed motor functions. The purpose of this study is to examine experimentally the fuzzy controller based on cycle-to-cycle control for FES-induced gait. A basic experimental test was performed on controlling maximum knee extension angle with normal subjects. In most of control trials, the joint angle was controlled well compensating changes in muscle responses to electrical stimulation. The results show that the fuzzy controller would be practical in clinical applications of gait control by FES. An automatic parameter tuning would be required practically for quick responses in reaching the target and in compensating the change in muscle responses without causing oscillating responses.

A parametric linear filter for a linear observation model usually requires a parameter selection process so that the filter achieves a better filtering performance. Generally, criteria for the parameter selection need not only the filtered solution but also the filter itself with each candidate of the parameter. Obtaining the filter usually costs a large amount of calculations. Thus, an efficient algorithm for the parameter selection is required. In this paper, we propose a fast parameter selection algorithm for linear parametric filters that utilizes a joint diagonalization of two non-negative definite Hermitian matrices.

The subspace algorithm can be utilized for the blind detection of space-time block codes (STBC) without knowledge of channel state information (CSI) both at the transmitter and receiver. However, its performance degrades when the channels are correlated. In this letter, we analyze the impact of channel correlation from the orthogonality loss between the transmit signal subspace (TSS) and the statistical noise subspace (SNS). Based on the decoding property of the subspace algorithm, we propose a revised detection in favor of the channel correlation matrix (CCM) only known to the receiver. Then, a joint transmit-receive preprocessing scheme is derived to obtain a further performance improvement when the CCM is available both at the transmitter and receiver. Analysis and simulation results indicate that the proposed methods can significantly improve the blind detection performance of STBC over the correlated channels.

The most time consuming operation to verify a signature with the Elliptic Curve Digital Signature Algorithm is a multi-scalar multiplication with two scalars. Efficient methods for its computation are the Shamir method and the Interleave method, whereas the performance of those methods can be improved by using general base-2 representations of the scalars. In exchange for the speed-up, those representations require the precomputation of several points that must be stored. In the case of two precomputed points, the Interleave method and the Shamir method provide the same, optimal efficiency. In the case of more precomputed points, only the Interleave method can be sped-up in an optimal way and is currently more efficient than the Shamir method. This paper proposes a new general base-2 representation of the scalars that can be used to speed up the Shamir method. It requires the precomputation of ten points and is more efficient than any other representation that also requires ten precomputed points. Therefore, the proposed method is the first to improve the Shamir method such that it is faster than the Interleave method.

Two versions of Krylov subspace order reduction techniques for VLSI interconnect reductions, including structure preserving reductions approach and adjoint networks approach, will be comparatively investigated. Also, we will propose a modified structure preserving reduction algorithm to speed up the projection construction in a linear order. The numerical experiment shows the high accuracy and low computational consumption of the modified method. In addition, it will be shown that the projection subspace generated from the structure-preserving approach and those from the adjoint networks approach are equivalent. Therefore, transfer functions of both reduced networks are identical.

We investigate the usefulness of the topology optimization with the finite element method in the optimization of an H-plane waveguide component. Design sensitivity is computed efficiently using the adjoint variable method. Employing the optimization procedure, optimized structures of an H-plane waveguide filter and T-junction are obtained from an initial homogeneous structure.

In this paper we study the problem of how to identify multiple disjoint paths that have the minimum total cost OPT and satisfy a delay bound D in a graph G. This problem has lots of applications in networking such as fault-tolerant quality of service (QoS) routing and network-flow load balancing. Recently, several approximation algorithms have been developed for this problem. Here, we propose a new approximation algorithm for it by using the Lagrangian Relaxation method. We then present a simple approximation algorithm for finding multiple link-disjoint paths that satisfy the delay constraints at a reasonable total cost. If the optimal solution under delay-bound D has a cost OPT, then our algorithm can find a solution whose delay is bounded by (1+)D and the cost is no more than (1+k)OPT. The time complexity of our algorithm is much better than the previous algorithms.

Accurate thickness measurement of sheet-like structure such as articular cartilage in CT images is required in clinical diagnosis as well as in fundamental research. Using a conventional measurement method based on the zero-crossing edge detection (zero-crossings method), several studies have already analyzed the accuracy limitation on thickness measurement of the single sheet structure that is not influenced by peripheral structures. However, no studies, as of yet, have assessed measurement accuracy of two adjacent sheet structures such as femoral and acetabular cartilages in the hip joint. In this paper, we present a model of the CT scanning process of two parallel sheet structures separated by a small distance, and use the model to predict the shape of the gray-level profiles along the sheet normal orientation. The difference between the predicted and the actual gray-level profiles observed in the CT data is minimized by refining the model parameters. Both a one-by-one search (exhaustive combination search) technique and a nonlinear optimization technique based on the Levenberg-Marquardt algorithm are used to minimize the difference. Using CT images of phantoms, we present results showing that when applying the one-by-one search method to obtain the initial values of the model parameters, Levenberg-Marquardt method is more accurate than zero-crossings and one-by-one search methods for estimating the thickness of two adjacent sheet structures, as well as the thickness of a single sheet structure.

In this paper, we propose an algorithm that solves the node-to-node disjoint paths problem in n-burnt pancake graphs in polynomial-order time of n. We also give a proof of its correctness as well as the estimates of time complexity O(n3) and the maximum path length 3n+4. We conducted a computer experiment for n=2 to 100 to measure the average performance of our algorithm. The results show that the average time complexity is O(n3.0) and the maximum path length is 3n+4.

We investigated relations between torque and elbow joint angle for constant muscle activations in isovelocity flexion movements of the forearm in three normal subjects. The reference angular velocity was from 0 to 90°/s and the applied torque from 0 to 15% of maximum voluntary contraction. Integrated surface electromyograms (IEMGs) of six muscles, torque, angle and angular velocity of the elbow joint were measured. A mathematical model describing the relationship between these variables was constructed with an artificial neural network. We estimated elbow joint torque by presenting different elbow joint angles, constant IEMGs and constant angular velocity to the model. For elbow joint angles greater than 60°, the slope, which was defined as the rate of torque increase with respect to elbow joint angle, was negative. For elbow joint angles less than 50°, the slope changed from positive to negative when the angular velocity increased. This implied that the flexor muscle-elbow joint system could change from unstable to stable when the angular velocity increased.

Irregular Repeat-Accumulate (IRA) codes, introduced by Jin et al., have a linear-time encoding algorithm and their decoding performance is comparable to that of irregular low-density parity-check (LDPC) codes. Meanwhile the authors have introduced detailedly represented irregular LDPC code ensembles specified with joint degree distributions between variable nodes and check nodes. In this paper, by using density evolution method [7],[8], we optimize IRA codes specified with joint degree distributions. Resulting codes have higher thresholds than Jin's IRA codes.

This paper describes optimization of H10-to- E01 mode converter by way of a right-angle E-plane junction (RAJ) between a rectangular waveguide and a circular waveguide in a waveguide rotary joint. Requirements for the optimized mode converter are formulated to provide the conjugate matching condition and analytical formulas for the rotary joint. A novel design procedure of the mode converter is proposed. An excellent performance of the mode converter fabricated for the Ka-band rotary joint is proved by computer simulation and the experimental results. The return loss and the insertion loss rotational effect are less than -25 dB and 0.02 dB in the 10% bandwidth, respectively.

In this paper, we give an algorithm for the node-to-set disjoint paths problem in a transposition graph. The algorithm is of polynomial order of n for an n-transposition graph. It is based on recursion and divided into two cases according to the distribution of destination nodes. The maximum length of each path and the time complexity of the algorithm are estimated theoretically to be O(n7) and 3n - 5, respectively, and the average performance is evaluated based on computer experiments.

A novel approach of robust adaptive beamforming (RABF) is presented in this paper, aiming at robustness against both finite-sample effects and steering vector mismatches. It belongs to the class of diagonal loading approaches with the loading level determined based on worst-case performance optimization. The proposed approach, however, is distinguished by two points. (1) It takes finite-sample effects into account and applies worst-case performance optimization to not only the constraints, but also the objective of the constrained quadratic equation, for which it is referred to as joint worst-case RABF (JW-RABF). (2) It suggests a simple closed-form solution to the optimal loading after some approximations, revealing how different factors affect the loading. Compared with many existing methods in this field, the proposed one achieves better robustness in the case of small sample data size as well as steering vector mismatches. Moreover, it is less computationally demanding for presenting a simple closed-form solution to the optimal loading. Numerical examples confirm the effectiveness of the proposed approach.