With the proliferation of multimedia group applications, the construction of multicast trees satisfying the Quality of Service (QoS) requirements is becoming a problem of the prime importance. An essential factor of these real-time application is to optimize the Delay- and delay Variation-Bounded Multicast Tree (DVBMT) problem. This problem is to satisfy the minimum delay variation and the end-to-end delay within an upper bound. The DVBMT problem is known as NP-complete problem. The representative algorithms for the problem are DVMA, DDVCA, and so on. In this paper, we show that the proposed algorithm outperforms any other algorithm. The efficiency of our algorithm is verified through the performance evaluation and the enhancement is up to about 13.5% in terms of the multicast delay variation. The time complexity of our algorithm is O(mn2) which is comparable to well known DDVCA.

The H.264 standard allows each macroblock to have up to sixteen motion vectors, four reference frames, and a macroblock mode. Exploiting this feature, we present an efficient temporal error concealment algorithm for H.264-coded video. The proposed method turns out to show good performance compared with conventional approaches.

This paper presents a method of simple adaptive control (SAC) using neural networks for a class of nonlinear systems with bounded-input bounded-output (BIBO) and bounded nonlinearity. The control input is given by the sum of the output of the simple adaptive controller and the output of the neural network. The neural network is used to compensate for the nonlinearity of the plant dynamics that is not taken into consideration in the usual SAC. The role of the neural network is to construct a linearized model by minimizing the output error caused by nonlinearities in the control systems. Furthermore, convergence and stability analysis of the proposed method is performed. Finally, the effectiveness of the proposed method is confirmed through computer simulation.

We propose an optimal algorithm for the real-time scheduling of parallel tasks on multiprocessors, where the tasks have the properties of flexible preemption, linear speedup, bounded parallelism, and arbitrary deadline. The proposed algorithm is optimal in the sense that it always finds out a feasible schedule if one exists. Furthermore, the algorithm delivers the best schedule consuming the fewest processors among feasible schedules. In this letter, we prove the optimality of the proposed algorithm. Also, we show that the time complexity of the algorithm is O(M2N2) in the worst case, where M and N are the number of tasks and the number of processors, respectively.

This paper proposes a new class of parallel branch-and-bound (B&B) schemes. The main idea of the scheme is to focus on the functional parallelism instead of conventional data parallelism, and to support such a heterogeneous and irregular parallelism by using a collection of autonomous agents distributed over the network. After examining several implementation issues, we describe a detail of the prototype system implemented over eight PC's connected by a network. The result of experiments conducted over the prototype system indicates that the proposed parallel processing scheme significantly improves the performance of the underlying B&B scheme by adaptively switching exploring policies adopted by each agent participating to the problem solving.

We discuss the problem of finding a dominant sequence for sending input data items from a low-end client to a server for computational intensive tasks under the realistic assumption of unpredictable communication behavior. Under this assumption, the client has to send the input data items using a specified sequence to maximize the number of computations performed by the server at any time. The sequence-finding problem is NP-hard for the general case. In this paper, we address three fundamental and useful applications: the product of two polynomials, matrices multiplication and Fast Fourier Transform. We show that the sequence-finding problems of the three applications can be solved optimally in linear time. However, we also show counter examples to rule out any possibility of finding a dominant sequence for sparse cases of the three applications. Finally, a simulation is conducted to show the usefulness of our method.

In this paper, we treat a design problem for IIR digital filters described by rational transfer function in discrete space. First, we form the filter design problem using the modified least-squares (MLS) criterion and express it as the quadratic form with respect to the numerator and denominator coefficients. Next, we show the relaxation method using the Lagrange multiplier method in order to search for the good solution efficiently. Additionally we can check the filter stability when designing the denominator coefficients. Finally, we show the effectiveness of the proposed method using a numerical example.

For various applications in image, communications and signal processing, two-dimensional (2-D) generalized orthogonal (GO) sequences, that is, 2-D sequences with zero correlation zone (ZCZ) and 2-D complementary orthogonal (CO) sequences with ZCZ, are widely investigated. New lower bounds for 2-D GO sequences, based on matrix theory on rank, are derived and presented, some examples that attain these lower bounds are given. As a direct application to our results, upper bound on family size of 2-D mutually complementary orthogonal (MCO) codes defined by Luke [9] is proposed.

This letter presents robustness bounds (RBs) for receding horizon controls (RHCs) of uncertain systems. The proposed RBs are obtained easily by solving convex problems represented by linear matrix inequalities (LMIs). We show, by numerical examples, that the RHCs can guarantee robust stabilization for a larger class of uncertain systems than conventional linear quadratic regulators (LQRs).

Sequences with ear zero correlation zones (EZCZs) are employed to suppress inter-symbol interference (ISI) and inter-user interference (IUI) in wireless communications. Theoretical limits on correlation functions of such sequences are investigated, lower bounds on the relations among length of sequence, width of EZCZs/ELCZs and family size are derived and presented, which play an important role in assessing performance of such sequences.

This letter considers the signal design problems for quaternary digital communications with nonuniform sources. The designs are considered for both the average and equal energy constraints and for a two-dimensional signal space. A tight upper bound on the bit error probability (BEP) is employed as the design criterion. The optimal quarternary signal sets are presented and their BEP performance is compared with that of the standard QPSK and the binary signal set previously designed for nonuniform sources. Results shows that a considerable saving in the transmitted power can be achieved by the proposed average-energy signal set for a highly nonuniform source.

For producing high quality synthesis, a concatenation-based Text-to-Speech (TTS) system usually requires a large number of segmental units to cover various acoustic-phonetic contexts. However, careful manual labeling and segmentation by human experts, which is still the most reliable way to prepare such units, is labor intensive. In this paper we adopt a two-step procedure to automate the labeling, segmentation and refinement process. In the first step, coarse segmentation of speech data is performed by aligning speech signals with the corresponding sequence of Hidden Markov Models (HMMs). Then in the second step, segment boundaries are refined with a proposed Context-Dependent Boundary Model (CDBM). Classification and Regression Tree (CART) is adopted to organize available data into a structured hierarchical tree, where acoustically similar boundaries are clustered together to train tied CDBM models for boundary refinement. Optimal CDBM parameters and training conditions are found through a series of experimental studies. Comparing with manual segmentation reference, segmentation accuracy (within a tolerance of 20 ms) is improved by the CDBMs from 78.1% (baseline) to 94.8% in Mandarin Chinese and from 81.4% to 92.7% in English, with about 1,000 manually segmented sentences used in training the models. To further reduce the amount of manual data for training CDBMs of a new speaker, we adapt a well-trained CDBM via efficient adaptation algorithms. With only 10-20 manually segmented sentences as adaptation data, the adapted CDBM achieves a segmentation accuracy of 90%.

An inverse scattering problem of estimating the surface impedance for an inhomogeneous half-space is investigated. By virtue of the fact that the far field representation contains the spectral function of the scattered field, complex values of the function are estimated from a set of absolute values of the far field. An approximate function for the spectral function is reconstructed from the estimated complex values by the least-squares sense. The surface impedance is estimated through calculating the field on the surface of the half-space expressed by the inverse Fourier transform. Numerical examples are given and the accuracy of the estimation is discussed.

Generalized impedance boundary conditions are employed to simulate the effects of the parallel-stratified media on electromagnetic fields. Sommerfeld type integral contained in Hertz potential is expressed as the sum of two parts: zeroth order Hankel function and an absolutely convergent series expansion of spherical Hankel functions.

In order to eliminate the co-channel and multi-path interference of quasi-synchronous code division multiple access (QS-CDMA) systems, spreading sequences with low or zero correlation zone (LCZ or ZCZ) can be used. The significance of LCZ/ZCZ to QS-CDMA systems is that, even there are relative delays between the transmitted spreading sequences due to the inaccurate access synchronization and the multipath propagation, the orthogonality (or quasi-orthogonality) between the transmitted signals can still be maintained, as long as the relative delay does not exceed certain limit. In this paper, several lower bounds on the aperiodic autocorrelation and crosscorrelation of binary LCZ/ZCZ sequence set with respect to the family size, sequence length and the aperiodic low or zero correlation zone, are derived. The results show that the new bounds are tighter than previous bounds for the LCZ/ZCZ sequences.

Interactive multimedia applications (IMAs) require not only adequate bandwidth to support large volume data transmission but also bounded end-to-end transmission delay between end users. This study proposes a Delay and Degree constrained Multicasting Spanning Tree (D2MST) algorithm to build an any-to-any share tree for IMAs. D2MST comprises root selection and spanning tree generation. A weighting function is defined based on the novel concept of network center and gravity to choose the root of a share tree. From the root, a spanning tree is built by incrementally connecting nodes with larger "power" to the tree so that the degree constraint is satisfied. Simulation results show that D2MST can successfully generate a Δ-constraint MST in which a high percentage of nodes can interact within the bounded delay.

In 1996, Sipser and Spielman [12] constructed a family of linear-time decodable asymptotically good codes called expander codes. Recently, Barg and Zemor [2] gave a modified construction of expander codes, which greatly improves the code parameters. In this paper we present a new simple algebraic decoding algorithm for the modified expander codes of Barg and Zemor, and give a Justesen-type construction of linear-time decodable asymptotically good binary linear codes that meet the Zyablov bound.

Using several high rate recursive convolutional codes as the basic element and the trace criteria as the designing principle, a new kind of recursive space-time trellis code with more flexible and higher data rate is presented for the serially concatenated space-time code. When 2b-ary modulation and N transmit antennas are used, the data rate of the new code can be arranged from b bps/Hz to Nb-1bps/Hz by modifying the number of recursive convolutional codes and the data rate of each code.

In order to control a sound field using multiple sources and microphones, we must choose the optimum values of parameters such as the numbers of sources and microphones, the location of the sources and the microphones and the filter tap length. Because there is a huge number of possible combinations of these conditions, the boundary surface control principle can be useful as a basis of a design method of such a system. In this paper, a design method of sound field reproduction and active noise control based on the BSC principle are described and several example of its application are presented.

Our goal in this paper is to provide a complete detection analysis for the OS processor along with OSGO and OSSO modified versions, for M postdetection integrated pulses when the operating environment is nonideal. Analytical results of performance are presented in both multiple-target situations and in regions of clutter power transitions. The primary and the secondary interfering targets are assumed to be fluctuating in accordance with the Swerling II target fluctuation model. As the number of noncoherently integrated pulses increases, lower threshold values and consequently better detection performances are obtained in both homogeneous and multiple target background models. However, the false alarm rate performance of OSSO-CFAR scheme at clutter edges is worsen with increasing the postdetection integrated pulses. As predicted, the OSGO-CFAR detector accommodates the presence of spurious targets in the reference window, given that their number is within its allowable range in each local window, and controls the rate of false alarm when the contents of the reference cells have clutter boundaries. The OSSO-CFAR scheme is useful in the situation where there is a cluster of radar targets amongst the estimation cells.