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.

Point pattern matching (PPM) arises in areas such as pattern recognition, digital video processing and computer vision. In this study, a novel Genetic Algorithm (GA) based method for matching affine-related point sets is described. Most common techniques for solving the PPM problem, consist in determining the correspondence between points localized spatially within two sets and then find the proper transformation parameters, using a set of equations. In this paper, we use this fact that the correspondence and transformation matrices are two unitary polar factors of Grammian matrices. We estimate one of these factors by the GA's population and then evaluate this estimation by computing an error function using another factor. This approach is an easily implemented one and because of using the GA in it, its computational complexity is lower than other known methods. Simulation results on synthetic and real point patterns with varying amount of noise, confirm that the algorithm is very effective.

In this paper, Morse code is selected as a communication adaptive device for persons whose hand coordination and dexterity are impaired by such ailments as amyotrophic lateral sclerosis, multiple sclerosis, muscular dystrophy, and other severe handicaps. Morse code is composed of a series of dots, dashes, and space intervals, and each element is transmitted by sending a signal for a defined length of time. A suitable adaptive automatic recognition method is needed for persons with disabilities due to their difficulty in maintaining a stable typing rate. To overcome this problem, the proposed method combines the support vector machines method with a variable degree variable step size LMS algorithm. The method is divided into five stages: tone recognition, space recognition, training process, adaptive processing, and character recognition. Statistical analyses demonstrated that the proposed method elicited a better recognition rate in comparison to alternative methods from the literature.

This paper investigates some relations among four complexities of sequence over countably infinite alphabet, and shows that two kinds of empirical entropies and the self-entropy rate regarding a Markov source are asymptotically equal and lower bounded by the maximum number of phrases in distinct parsing of the sequence. Some connections with source coding theorems are also investigated.

Developing embedded parallel image processing applications is usually a very hardware-dependent process, often using the single instruction multiple data (SIMD) paradigm, and requiring deep knowledge of the processors used. Furthermore, the application is tailored to a specific hardware platform, and if the chosen hardware does not meet the requirements, it must be rewritten for a new platform. We have proposed the use of design space exploration [9] to find the most suitable hardware platform for a certain application. This requires a hardware-independent program, and we use algorithmic skeletons [5] to achieve this, while exploiting the data parallelism inherent to low-level image processing. However, since different operations run best on different kinds of processors, we need to exploit task parallelism as well. This paper describes how we exploit task parallelism using an asynchronous remote procedure call (RPC) system, optimized for low-memory and sparsely connected systems such as smart cameras. It uses a futures [16]-like model to present a normal imperative C-interface to the user in which the skeleton calls are implicitly parallelized and pipelined. Simulation provides the task dependency graph and performance numbers for the mapping, which can be done at run time to facilitate data dependent branching. The result is an easy to program, platform independent framework which shields the user from the parallel implementation and mapping of his application, while efficiently utilizing on-chip memory and interconnect bandwidth.

In this letter we present steady-state analyses of a gradient algorithm (GA) for second-order adaptive infinite impulse response (IIR) notch filters. A method for deriving more accurate estimation mean square error (MSE) expressions than the recently proposed method is presented. The method is based on the estimation error power spectral density (PSD). Moreover, an expression for the estimation bias for the adaptive IIR notch filter with constrained poles and zeros is shown to be obtained from the estimation MSE expression. Simulations are presented to confirm the validity of the analyses.

This paper deals with questions concerning the supply of building-blocks (BBs) in the initial population of real-coded genetic algorithms (rGAs). Drawing upon the methodology of existing BB supply studies for finite alphabets, facetwise models for the supply of a single schema as well as for the supply of all the schemata in a partition are proposed. A model for the initial population size necessary to ensure the presence of all the raw BBs with a given supply error has also been developed using the partition success model. Experimental results show the effectiveness of the facetwise models and the initial population sizing model. Finally, an adaptation approach is suggested for practical use of the BB supply.

We extend the adaptive-order rational Arnoldi algorithm for multiple-inputs and multiple-outputs (MIMO) interconnect model order reductions. Instead of using the standard Arnoldi algorithm for the SISO adaptive-order reduction algorithm (AORA), we study the adaptive-order rational global Arnoldi (AORGA) algorithm for MIMO model reductions. In this new algorithm, the input matrix is treated as a vector form. A new matrix Krylov subspace, generated by the global Arnoldi algorithm, will be developed by a Frobenius-orthonormal basis. By employing congruence transformation with the matrix Krylov subspace, the one-sided projection method can be used to construct a reduced-order system. It will be shown that the system moment matching can be preserved. In addition, we also show that the transfer matrix residual error of the reduced system can be derived analytically. This error information will provide a guideline for the order selection scheme. The algorithm can also be applied to the classical multiple point MIMO Pade approximation by the rational Arnoldi algorithm for multiple expansion points. Experimental results demonstrate the feasibility and the effectiveness of the proposed method.

A hardware algorithm for computing the reciprocal of the Euclidean norm of a 3-dimensional (3-D) vector which appears frequently in 3-D computer graphics is proposed. It is based on a digit-recurrence algorithm for computing the Euclidean norm and an on-line division (on-line reciprocal computation) algorithm. These algorithms are modified, so that the reciprocal of the Euclidean norm is computed by performing on-line division where the divisor is the partial result of Euclidean norm computation. Division, square-rooting, and reciprocal square-root computation, which are important operations in 3-D graphics, can also be performed using a circuit based on the proposed algorithm.

This paper proposes a low power scan test scheme and formulates a problem based on this scheme. In this scheme the flip-flops are grouped into N scan chains. At any time, only one scan chain is active during scan test. Therefore, both average power and peak power are reduced compared with conventional full scan test methodology. This paper also proposes a tabu search-based approach to minimize test application time. In this approach we handle the information during deterministic test efficiently. Experimental results demonstrate that this approach drastically reduces both average power and peak power dissipation at a little longer test application time on various benchmark circuits.

This paper proposes the combination of adjustable architecture and parameter optimization software, employing a method based on artificial intelligence (AI), to realize an image rejection mixer (IRM) that can enhance its image rejection ratio within a short period of time. The main components of the IRM are 6 Gilbert-cell multipliers. The tail current of each multiplier is adjusted by the optimization software, and the gain and phase characteristics are optimized. This adjustment is conventionally extremely difficult because the 6 tail currents to be adjusted simultaneously are mutually interdependent. In order to execute this adjustment efficiently, we employed a Genetic Algorithm (GA) that is a robust search algorithm that can find optimal parameter settings in a short time. We have successfully developed an IRM chip that has a performance of 71 dB and is suitable for single-chip integration with WCDMA applications.

Recent work has shown that the usage of multiple antennas at the transmitter and receiver in a flat fading environment results in a linear increase in channel capacity. But increasing the number of antennas induces the higher hardware costs and computational burden. To overcome those problems, it is effective to select antennas appropriately among all available ones. In this paper, a new antenna selection method is proposed. The transmit antennas are selected so as to maximize the channel capacity using the genetic algorithm (GA) which is the one of the general random search algorithm. The results show that the proposed GA achieves almost the same performance as the optimal selection method with less computational amount.

In this paper, the voice signal processing module has been designed using the micro processor for the use of fully implantable middle ear devices (F-IMEHD). The voice signal processing module for F-IMEHD should be designed to compensate for the hearing loss of hearing impaired person and have the flexibility for compensating various hearing threshold level. So, the voice signal processing module has been designed and implemented to present the various frequency characteristics using the low-power micro processor, MSP430F169. The different voice signal path to the inner ear entrance was considered so that two voice signal would be combined in-phase using an all pass filter with a constant time-delay to improve the vibration of the ossicles.

We propose a sub-optimal but computationally efficient Modified Fano Detection algorithm (MFD) for V-BLAST systems. This algorithm utilizes the QR decomposition of the channel matrix and the sequential detection scheme based on tree searching to find the optimal symbol sequence. For more reliable signal detection, the decoder is designed to move backward for the specified value at the end of the tree. This results in significant reduction of the complexity while the performance of MFD is comparable to that of ML detector.

Electrical capacitance tomography (ECT) is used to obtain information about the distribution of a mixture of dielectric materials inside a vessel or pipe. ECT has several advantages over other reconstruction algorithms and has found many applications in the industrial fields. However, there are some difficulties with image reconstruction in ECT: The relationship between the permittivity distribution and measured capacitance is nonlinear. And inverse problem is ill-posed so that the inverse solution is sensitive to measurement error. To cope with these difficulties iterative image reconstruction algorithms have been developed. In general, the iterative reconstruction algorithms in ECT have comparatively good-quality in reconstructed images but result in intensive computational burden. This paper presents the iterative image reconstruction algorithm for ECT that can enhance the speed of image reconstruction without degradation in the quality of reconstructed image. The main contribution of the proposed algorithm is new weighting matrices, which are obtained by the interpolation of the grouped electrical field centre lines (EFCLs). Extensive simulation results have demonstrated that proposed algorithm provides improved reconstruction performance in terms of computational time and image quality.

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.

In this paper, a new dimming algorithm for the electronic ballast of an electrodeless fluorescent lamp is proposed. The proposed method is based on the burst dimming method that controls the duty ratio for the two switches of the electronic ballast by intermittently modulated pulse signal. This paper presents a fully digital circuit using an erasable programmable logic device (EPLD). To verify the validity of the proposed method, the implemented control circuit was applied to the electronic ballast for a 100 W electrodeless fluorescent lamp. As a result, a dimming method with a wide illumination range from 5 to 100% was obtained.

Let H be a graph with a designated vertex s, where edges are weighted by nonnegative reals. Splitting edges e={u,s} and e'={s,v} at s is an operation that reduces the weight of each of e and e' by a real δ>0 while increasing the weight of edge {u,v} by δ. It is known that all edges incident to s can be split off while preserving the edge-connectivity of H and that such a complete splitting is used to solve many connectivity problems. In this paper, we give an O(mn+n2log n) time algorithm for finding a complete splitting in a graph with n vertices and m edges.

In this paper, a 2-D iteratively reweighted least squares lattice algorithm, which is robust to the outliers, is introduced and is applied to defect detection problem in textured images. First, the philosophy of using different optimization functions that results in weighted least squares solution in the theory of 1-D robust regression is extended to 2-D. Then a new algorithm is derived which combines 2-D robust regression concepts with the 2-D recursive least squares lattice algorithm. With this approach, whatever the probability distribution of the prediction error may be, small weights are assigned to the outliers so that the least squares algorithm will be less sensitive to the outliers. Implementation of the proposed iteratively reweighted least squares lattice algorithm to the problem of defect detection in textured images is then considered. The performance evaluation, in terms of defect detection rate, demonstrates the importance of the proposed algorithm in reducing the effect of the outliers that generally correspond to false alarms in classification of textures as defective or nondefective.

Given a graph G=(V,E), a set of vertices S ⊆ V covers v ∈ V if the edge connectivity between S and v is at least a given number k. Vertices in S are called sources. The source location problem is a problem of finding a minimum-size source set covering all vertices of a given graph. This paper presents a new variation of the problem, called maximum-cover source-location problem, which finds a source set S with a given size p, maximizing the sum of the weight of vertices covered by S. It presents an O(np + m + nlog n)-time algorithm for k=2, where n=|V| and m=|E|. Especially it runs linear time if G is connected. This algorithm uses a subroutine for finding a subtree with the maximum weight among p-leaf trees of a given vertex-weighted tree. For the problem we give a greedy-based linear-time algorithm, which is an extension of the linear-time algorithm for finding a longest path of a given tree presented by E. W. Dijkstra around 1960. Moreover, we show some polynomial solvable cases, e.g., a given graph is a tree or (k-1)-edge-connected, and NP-hard cases, e.g., a vertex-cost function is given or G is a digraph.