In this paper, a hardware-oriented Genetic Algorithm (GA) was proposed in order to save the hardware resources and to reduce the execution time of GAP. Based on steady-state model among continuous generation model, the proposed GA used modified tournament selection, as well as special survival condition, with replaced whenever the offspring's fitness is better than worse-fit parent's. The proposed algorithm shows more than 30% in convergence speed over the conventional algorithm. Finally, by employing the efficient pipeline parallelization and handshaking protocol in proposed GAP, above 30% of the computation speed-up can be achieved over survival-based GA which runs one million crossovers per second (1 MHz), when device speed and size of application are taken into account on prototype. It would be used for high speed processing such of central processor of evolvable hardware, robot control and many optimization problems.

The explosive growth of World Wide Web usage is causing a number of performance problems, including slow response times, network congestion, and denial of service. Web site that has a huge number of accesses and requires high quality of services, such as a site offering hosting services, or content delivery services, usually uses a cache server to reduce the load on the original server offering the original content. To increase the throughput of the caching process and to improve service availability, multiple cache servers are often positioned in front of the original server. This requires a switch to direct incoming requests to one of the multiple cache servers. In this paper, we propose a routing algorithm for such a switch in front of clustered multiple cache servers and evaluate its performance by simulation. The results show that our routing algorithm is effective when content has request locality and a short period of validity, for example, news, map data, road traffic data, or weather information. We also identify points to consider when the proposed algorithm is applied to a real system.

When a randomized algorithm elects a leader on anonymous networks, initial information (which is called in general initial condition in this paper) of some sort is always needed. In this paper, we study common properties of initial conditions that enable a randomized algorithm to elect a leader. In the previous papers, the author introduced the notion of transformation between initial conditions using distributed algorithms. By using this notion of transformation, we investigate the property of initial conditions for the leader election. We define that an initial condition C is p(N)-complete if there exists some randomized algorithm that elects a leader with probability p(N) on any size N network satisfying C. We show that we can divide p(N)-completeness into four types as follows. 1. p(N)=1: For any 1-complete initial conditions, there exists a deterministic distributed algorithm that can compute the size of the network for any initial information satisfying the initial condition. 2. inf p(N) >0: For any p(N)-complete initial conditions with inf p(N) >0, there exists a deterministic distributed algorithm that can compute an upper-bound for the size of the network for any initial information satisfying the initial condition. 3. inf p(N) converges to 0: The set of p(N)-complete initial conditions varies depending on the decrease rate of p(N). 4. p(N) decreases exponentially: Any initial condition is regarded as p(N)-complete.

We propose new lossless medical image compression method based on hierarchical sorting technique. Hierarchical sorting is a technique to achieve high compression ratio by detecting the regions where image pattern varies abruptly and sorting pixel order by its value to increase predictability. In this method, we can control sorting accuracy along with size and complexity. As the result, we can reduce the sizes of the permutation-tables and reuse the tables to other image regions. Comparison using experimental implementation of this method shows better performance for medical image set measured by X-ray CT and MRI instruments where similar sub-block patterns appear frequently. This technique applies quad-tree division method to divide an image to blocks in order to support progressive decoding and fast preview of large images.

This paper studies effect of packet scheduling algorithms at routers on media synchronization quality in live audio and video transmission by experiment. In the experiment, we deal with four packet scheduling algorithms: First-In First-Out, Priority Queueing, Class-Based Queueing and Weighted Fair Queueing. We assess the synchronization quality of both intra-stream and inter-stream with and without media synchronization control. The paper clarifies the features of each algorithm from a media synchronization point of view. A comparison of the experimental results shows that Weighted Fair Queueing is the most efficient packet scheduling algorithm for continuous media among the four.

In functional brain images obtained by analyzing higher human brain functions using functional magnetic resonance imaging (fMRI), one serious problem is that these images depict false activation areas (artifacts) resulting from image-to-image physiological movements of subject during fMRI data acquisition. In order to truly detect functional activation areas, it is necessary to eliminate the effects of physiological movements of subject (i.e., gross head motion, pulsatile blood and cerebrospinal fluid (CSF) flow) from fMRI time series data. In this paper, we propose a method for eliminating artifacts due to not only rigid-body motion such as gross head motion, but also non-rigid-body motion like the deformation caused by the pulsatile blood and CSF flow. The proposed method estimates subject movements by using gradient methods which can detect subpixel optical flow. Our method estimates the subject movements on a "pixel-by-pixel" basis, and achieves the accurate estimation of both rigid-body and non-rigid-body motion. The artifacts are reduced by correction based on the estimated movements. Therefore, brain activation areas are accurately detected in functional brain images. We demonstrate that our method is valid by applying it to real fMRI data and that it can improve the detection of brain activation areas.

In this paper we addresses the problem of finding feasible solutions for the Group Multicast Routing Problem (GMRP). This problem is a generalization of the multicast routing problem whereby every member of the group is allowed to multicast messages to other members from the same group. The routing problem involves the construction of a set of low cost multicast trees with bandwidth requirements for all the group members in the network. We first prove that the problem of finding feasible solutions to GMRP is NP-complete. Following that we propose a new heuristic algorithm for constructing feasible solutions for GMRP. Simulation results show that our proposed algorithm is able to achieve good performance in terms of its ability of finding feasible solutions whenever one exist.

An algorithm based on the wavelet transform (WT) was developed to analyze the QRS complex in a three-dimensional magnetocardiogram (3-D MCG) recorded from 3 normal subjects and 1 patient with anterior myocardial infarction (MI). By using a wavelet equivalent filter constructed with the WT algorithm, the high frequency components of the QRS complex related to the late fields (LF) were detected for the patient with anterior MI at different scale. We quantified the high frequency components of the QRS complex by calculating root-mean-square (RMS) value at different scale. The LF mainly existed in the frequency band of about 35.5 to 110.5 Hz with the amplitude of about 0.1 to 0.4 pT for Bx, By, and Bz components. In order to discuss the activities of the heart between the normal subject and the patient with anterior MI, we have also evaluated the spatial energy distribution (SED) of the QRS complex by displaying isoenergy contour maps at different scale. Being different from the normal subject, the patient with anterior MI represented different the pattern of the SED in various frequency band for the ST segment of the QRS complex of Bx, By, and Bz components. It is efficient to use the WT algorithm for analyzing the QRS complex in the 3-D MCG.

We propose a new and fast full search (FS) motion estimation algorithm for video coding. The computational reduction comes from sequential rejection of impossible candidates with derived formula and subblock norms. Our algorithm reduces more the computations than the recent fast full search (FS) motion estimation algorithms.

In this paper, genetic algorithms is employed to determine the shape of a conducting cylinder buried in a half-space. Assume that a conducting cylinder of unknown shape is buried in one half-space and scatters the field incident from another half-space where the scattered filed is measured. Based on the boundary condition and the measured scattered field, a set of nonlinear integral equations is derived and the imaging problem is reformulated into an optimization problem. The genetic algorithm is then employed to find out the nearly global extreme solution of the object function such that the shape of the conducting scatterer can be suitably reconstructed. In our study, even when the initial guess is far away from the exact one, the genetic algorithm can avoid the local extremes and converge to a reasonably good solution. In such cases, the gradient-based methods often get stuck in local extremes. Numerical results are presented and good reconstruction is obtained both with and without the additive Gaussian noise.

In order to maintain the diversity of structures in the population and prevent premature convergence, I have developed a new genetic algorithm called DCGA. In the experiments on many standard benchmark problems, DCGA showed good performances, whereas with harder problems, in some cases, the phenomena were observed that the search was stagnated at a local optimum despite that the diversity of the population is maintained. In this paper, I propose methods for escaping such phenomena and improving the performance by reinitializing the population, that is, a method called each-structure-based reinitializing method with a deterministic structure diverging procedure as a method for producing new structures and an adaptive improvement probability bound as a search termination criterion. The results of experiments demonstrate that DCGA becomes robust in harder problems by employing these proposed methods.

An improved algorithm is developed for correcting the topographic impact on satellite imagery. First, we analyze the topography induced distortion on satellite image. It is shown that the variation of aspect can cause the obvious different distortions in the remotely sensed image, and also effect the image illumination significantly. Because the illumination is the basis for topographic correction algorithms, we consider its variation in different sun-facing aspects in calculation a correction parameter and take it as a key element in the modified correction algorithm. Then, we apply the modified correction method on the actual Landsat Thematic Mapper satellite image. The topographic correction was done in different image data with different season and different solar angle. The corrected results show the effectiveness and accuracy using this approach.

Synthetic aperture radar interferometry have been established in the past two decades, and used extensively for many applications including topographic mapping of terrain and surface deformation. Vegetation analysis is also a growing area of its application. In this paper, we propose an polarimetric SAR interferometry technique for interferometric phase extraction of each local scatterer. The estimated position of local scattering centers has an important information for effective tree height estimation of forest. The proposed method formulated for local scattering center extraction is based on the ESPRIT algorithm which is known for high-resolution capability of closely located incident waves. The method shows high-resolution performance when local scattered waves are uncorrelated and have different polarization characteristics. Using the method, the number of dominant local scattering centers and interferometric phases in each image pixel can be estimated directly. Validity of the algorithm is demonstrated by using examples derived from SIR-C data.

In this paper, we propose a frequency domain active noise control (ANC) system without a secondary path model. The proposed system is based on the frequency domain simultaneous perturbation (FDSP) method we have proposed. In this system, the coefficients of the adaptive filter are updated only by error signals. The conventional ANC system using the filtered-x algorithm becomes unstable due to the error between the secondary path, from secondary source to error sensor, and its model. In contrast, the proposed ANC system has the advantage not to use the model. In this paper, we show the principle of the proposed ANC system, and examine its efficiency through computer simulations.

This paper proposes a non-linear adaptive algorithm, the amplitude banded RLS (ABRLS) algorithm, as an adaptation procedure for time variant channel equalizers. In the ABRLS algorithm, a coefficient matrix is updated based on the amplitude level of the received sequence. To enhance the capability of tracking for the ABRLS algorithm, a parallel adaptation scheme is utilized which involves the structures of decision feedback equalizer (DFE). Computer simulations demonstrate that the novel ABRLS based equalizer provides a significant improvement relative to the conventional RLS DFE on a rapidly time variant communication channel.

An automated analog circuit synthesis based on reuse of topological features of 'prototype circuits' is proposed. The prototype circuits are designed by humans and suggested to the synthesis system as hints of configurations of new analog circuits to be synthesized by the system. The connections of elements in analog circuits are not generally systematic, but they would have some similarities to a circuit which has similar behaviors or functionalities. In the proposed process, the information on circuit connections is stored as sub-circuits extracted from the prototype circuits. And then, genetic algorithm is used to search for an optimum combination of the sub-circuits that achieves the desired electronic specifications. The combinations of sub-circuits are performed with a novel technique where the terminals of the sub-circuits are shared. The capabilities of the proposed method are demonstrated through an example of the synthesis.

In this paper we present two contributions for a set of local transformations (a selection set) to improve a performance of a very large circuit. The first contribution is an idea of "padding node" and "multi-separator-set. " We have proven that combination of padding node and multi-separator-set provides the optimum selection set. The second contribution is our heuristic method to find a semi-optimum multi-separator-set, which uses a network flow algorithm. Our method is robust for very large circuits, because its memory usage and calculation time are linear and polynomial order with the size of the circuit. We have compared our method with Singh's selection function method, which provides the optimum selection set and is the best method in literature to date. Our method has successfully optimized delays of all circuits, while Singh's selection function method has aborted with three large circuits because of memory overflow. The results also has shown our method has a comparable capability in delay optimization to Singh's method, although our method is heuristic.

This paper proposes the Vector Evaluated GA-ICT (VEGA-ICT), a novel design method that employs the Genetic Algorithm (GA) to obtain the optimum antenna design. GA-ICT incorporates an arbitrary wire-grid model antenna to derive the optimum solution without any basic structure or limitation on the number of elements by merely optimizing an objective function. GA-ICT comprises the GA and an analysis method, the Improved Circuit Theory (ICT), with the following characteristics. (1) To achieve optimization of an arbitrary wire-grid model antenna without a basic antenna structure, the unknowns of the ICT are directly assigned to variables of the GA in the GA-ICT. (2) To achieve a variable number of elements, duplicate elements generated by using the same feasible region are deleted in the ICT. (3) To satisfy all complex design conditions, the GA-ICT generates an objective function using a weighting function generated based on electrical characteristics, antenna configuration, and size. (4) To overcome the difficulty of convergence caused by the nonlinearity of each term in the objective function, GA-ICT adopts a vector evaluation method. In this paper, the novel GA-ICT method is applied to downsize sector antennas. The calculation region in GA-ICT is reduced by adopting cylindrical coordinates and a periodic imaging structure. The GA-ICT achieves a 30% reduction in size compared to the previously reported small sector antenna, MS-MPYA, while retaining almost the same characteristics.

We present a simple cell scheduling algorithm for an input buffered switch. The suggested algorithm is based on iSLIP and consists of request, grant and accept steps. The pointer update scheme of iSLIP is simplified in the suggested algorithm. By virtue of the new update scheme, the performance of the suggested algorithm is better than that of iSLIP with one iteration. Using computer simulations under a uniform traffic, we show the suggested algorithm is more appropriate than iSLIP for scheduling of an input buffered switch with multiple service classes.

First, we give a graph-theoretic formalization for the spare assignment problems for two cases of reconfiguring NN mesh-connected processor arrays with spares on a diagonal line in the array or two orthogonal lines at the edges of the array. Second, we discuss the problems for minimizing the numbers of "dangerous processors" for the cases. Here, a dangerous processor is a nonfaulty one for which there remains no spare processor to be assigned if it becomes faulty, without modifying the spare assignments to other faulty processors. The problem for the latter case, originally presented by Melhem, has already been discussed and solved by the O(N2) algorithm in [3], but it's procedure is very complicated. Using the above graph-theoretic formalization, we give efficient plain algorithms for minimizing the numbers of dangerous processors by which the problems for both the cases can be solved in O(N) time.