This paper deals with the Optimum Communication Spanning Tree Problem (OCST) which is well known as an NP-hard problem. For solving the problem, we uses an evolutionary approach. This paper presents a new effective tree encoding and proposes a tree construction routine (TCR) to generate a tree from the encoding. The basic principle is to break a cycle. We also propose a new crossover operator that focuses on the inheritance of parental information and the use of network information. Consequently, we confirm that the proposed algorithm is superior to other algorithms applied to the OCST problem or other tree problems. Moreover, our method can find a better solution than the solution which was previously known as the best solution. In addition, we analyzed the locality and diversity property of encoding and observed that the proposed method has high locality and at the same time it preserves population diversity for many generations. Finally, we conclude that these properties are the main reasons why the proposed method outperforms the other encodings.

An algorithm for encoding low-density parity check (LDPC) codes is investigated. The algorithm computes parity check symbols by solving a set of sparse equations, and the triangular factorization is employed to solve the equations efficiently. It is shown analytically and experimentally that the proposed algorithm is more efficient than the Richardson's encoding algorithm if the code has a small gap.

Nonlinear modeling of complex irregular systems constitutes the essential part of many control and decision-making systems and fuzzy logic is one of the most effective algorithms to build such a nonlinear model. In this paper, a new approach to fuzzy modeling is proposed. The model considered herein is the well-known Sugeno-type fuzzy system. The fuzzy modeling algorithm suggested in this paper is composed of two phases: coarse tuning and fine tuning. In the first phase (coarse tuning), a successive clustering algorithm with the fuzzy validity measure (SCFVM) is proposed to find the number of the fuzzy rules and an initial fuzzy model. In the second phase (fine tuning), a moving genetic algorithm with partial encoding (MGAPE) is developed and used for optimized tuning of membership functions of the fuzzy model. Two computer simulation examples are provided to evaluate the performance of the proposed modeling approach and compare it with other modeling approaches.

This paper describes the efficiency of VLSI architecture for UMHexagonS (hybrid Unsymmetrical cross Multi Hexagon grid Search) matching algorithm. This algorithm is used for ME (Motion Estimation) of H.264/AVC video compression standard. The UMHexagonS is called a hybrid algorithm since it uses different kinds of searching patterns. VLSI architecture based on UMHexagonS is designed to provide a good tradeoff between gate sizes and high throughput. We implemented this architecture with about 309 K gates and 1/1792 throughput [block/cycle] for a search range of 16 and 44 macro blocks using synthesizable Verilog HDL.

We report a specially designed encoding technique for sign language video sequences supposing that the technique is for sign telecommunication such as that using mobile videophones with a low bitrate. The technique is composed of three methods: gradient coding, precedence macroblock coding, and not-coded coding. These methods are based on the idea to distribute a certain number of bits for each macroblock according to the evaluation of importance of parts of the picture. They were implemented on a computer and encoded data of a short clip of sign language dialogue was evaluated by deaf subjects. As a result, the efficiency of the technique was confirmed.

A baseband transmission scheme for wireless communications has been proposed and examined using a pair of discone antennas for transmission and reception. The wireless baseband transmission scheme radiates a baseband signal stream, such as non-return-to-zero (NRZ), return-to-zero (RZ), or Manchester encoded signals, directly from an antenna. Namely, a carrier in terms of a sinusoidal radio wave or light wave is not used in the transmission. In experiments, baseband pulses generated with a data generator were radiated directly from the discone antenna, and received waveforms were observed with a digital storage oscilloscope. The experiments showed that wireless baseband transmission is realisable when using antennas with a flat amplitude spectrum and a linear phase characteristic, such as discone antennas, over a given band. Manchester encoding is promising for this wireless baseband transmission.

Genetic Algorithm (GA) and other Evolutionary Algorithms (EAs) have been successfully applied to solve constrained minimum spanning tree (MST) problems of the communication network design and also have been used extensively in a wide variety of communication network design problems. Choosing an appropriate representation of candidate solutions to the problem is the essential issue for applying GAs to solve real world network design problems, since the encoding and the interaction of the encoding with the crossover and mutation operators have strongly influence on the success of GAs. In this paper, we investigate a new encoding crossover and mutation operators on the performance of GAs to design of minimum spanning tree problem. Based on the performance analysis of these encoding methods in GAs, we improve predecessor-based encoding, in which initialization depends on an underlying random spanning-tree algorithm. The proposed crossover and mutation operators offer locality, heritability, and computational efficiency. We compare with the approach to others that encode candidate spanning trees via the Pr?fer number-based encoding, edge set-based encoding, and demonstrate better results on larger instances for the communication spanning tree design problems.

In order to improve the efficiency and speed of match seeking in fractal compression, this paper presents an Average-Variance function which can make the optimal choice more efficiently. Based on it, we also present a fast optimal choice fractal image compression algorithm and an optimal method of constructing data tree which greatly improve the performances of the algorithm. Analysis and experimental results proved that it can improve PSNR over 1 dB and improve the coding speed over 30-40% than ordinary optimal choice algorithms such as algorithm based on center of gravity and algorithm based on variance. It can offer much higher optimal choice efficiency, higher reconstructive quality and rapid speed. It's a fast fractal encoding algorithm with high performances.

In this paper, we propose alternate self shielding to remove critical transitions of on-chip global interconnect. Our proposed method alternates shield and signal wires cycle by cycle. The conventional self-shielding methods need additional wires to remove critical transition by encoding. The proposed alternate self-shielding, however, requires no additional wires. We evaluate our method by simulating signal transimission with a circuit simulator. As a result, our proposed method is superior in bit rate compared to others from 10% to 75%.

Although a proposed steganographic encoding scheme can reduce distortion caused by data hiding, it makes the system susceptible to active-warden attacks due to error spreading. Meanwhile, straightforward application of error correction encoding inevitably increases the required amount of bit alterations so that the risk of being detected will increase. To overcome the drawback in both cases, an integrated approach is introduced that combines the stego-encoding and error correction encoding to provide enhanced robustness against active attacks and channel noise while keeping good imperceptibility.

Energy consumption is one of the most critical constraints in the current VLSI system designs. In addition, fault tolerance of VLSI systems will be also one of the most important requirements in the future shrunk VLSIs. This paper proposes practical low power and fault tolerant bus encoding methods in on-chip data transfer. The proposed encoding methods use the combination of simple low power code and fault tolerant code. Experimental results show that the proposed methods can reduce signal transitions by 23% on the bus with fault tolerance. In addition, circuit implementation results with bus signal swing optimization show the effectiveness of the proposed encoding methods. We show also the selection methodology of the optimum encoding method under the given requirements.

This paper proposes a genetically inspired adaptive clustering algorithm for numerical and categorical data sets. To this end, unique encoding method and fitness functions are developed. The algorithm automatically discovers the actual number of clusters and efficiently performs clustering without unduly compromising cluster-purity. Moreover, it outperforms existing clustering algorithms.

The encoding process of vector quantization (VQ) is a time bottleneck preventing its practical applications. In order to speed up VQ encoding, it is very effective to use lower dimensional features of a vector to estimate how large the Euclidean distance between the input vector and a candidate codeword could be so as to reject most unlikely codewords. The three popular statistical features of the average or the mean, the variance, and L2 norm of a vector have already been adopted in the previous works individually. Recently, these three statistical features were combined together to derive a sequential EEENNS search method in [6], which is very efficient but still has obvious computational redundancy. This Letter aims at giving a mathematical analysis on the results of EEENNS method further and pointing out that it is actually unnecessary to use L2 norm feature anymore in fast VQ encoding if the mean and the variance are used simultaneously as proposed in IEENNS method. In other words, L2 norm feature is redundant for a rejection test in fast VQ encoding. Experimental results demonstrated an approximate 10-20% reduction of the total computational cost for various detailed images in the case of not using L2 norm feature so that it confirmed the correctness of the mathematical analysis.

Since the inception of Globally Asynchronous Locally Synchronous (GALS) VLSI design, GALS has been considered a promising design technique for multi-clock-domain System-on-Chip (SoC). Among the handshake protocols available for SoC design, delay insensitive (DI) handshake protocol is becoming a core technology, since it facilitates robust data transfer regardless of wire delay variation. In this paper, a new data encoding scheme Differential Value Encoding (DVE) is proposed for two-phase 1-of-N DI handshake protocol. Compared with the conventional data encoding method, the proposed scheme effectively reduces the crosstalk effect on wires sending sequentially increasing data patterns, resulting in reduction of the data transfer time. Simulation results with SPEC CPU 2000 benchmarks and sequentially increasing data pattern reveal that the DVE scheme can reduce the crosstalk effect by tens of percentage and significantly decrease the data transfer time.

This paper presents new encoding methods for the binary genetic algorithm (BGA) and new converting methods for the real-coded genetic algorithm (RCGA). These methods are developed for the specific case in which some parameters have to be searched in wide ranges since their actual values are not known. The oversampling effect which occurs at large values in the wide range search are reduced by adjustment of resolutions in mantissa and exponent of real numbers mapped by BGA. Owing to an intrinsic similarity in chromosomal operations, the proposed encoding methods are also applied to RCGA with remapping (converting as named above) from real numbers generated in RCGA. A simple probabilistic analysis and benchmark with two ill-scaled test functions are carried out. System identification of a simple electrical circuit is also undertaken to testify effectiveness of the proposed methods to real world problems. All the optimization results show that the proposed encoding/converting methods are more suitable for problems with ill-scaled parameters or wide parameter ranges for searching.

We extend the differential space time block code (STBC) using nonconstant modulus constellations of two transmit antennas to four transmit antennas case. The proposed method obtains larger minimum Euclidean distances than those of conventional differential STBC with PSK constellations. We derive the symbol error rate (SER) performance of the proposed method and demonstrate the SER performance using computer simulations for both static and fast fading channels. For transmission rates greater than 2 bits/channel use and 3 bits/channel use, the proposed method outperforms the conventional differential STBC.

This paper presents the definition and implementation design of a low power data bus encoding scheme dedicated to system on chip video architectures. Trends in CMOS technologies focus the attention on the energy consumption issue related to on-chip global communication; this is especially true for data dominated applications such as video processing. Taking into account scaling effects a novel coupling-aware bus power model is used to investigate the statistical properties of video data collected in the system bus of a reference hardware/software H.263/MPEG-4 video coder architecture. The results of this analysis and the low complexity requirements drive the definition of a bus encoding scheme called CDSPBI (Coupling Driven Separated Partial Bus Invert), optimized ad-hoc for video data. A VLSI implementation of the coding circuits completes the work with an area/delay/power characterization that shows the effectiveness of the proposed scheme in terms of global power saving for a small circuit area overhead.

In this paper, we propose a progressive encoding algorithm for binary voxel models, which represent 3D object shapes. For progressive transmission, multi-resolution models are generated by decimating an input voxel model. Then, each resolution model is encoded by employing the pattern code representation(PCR). In PCR, the voxel model is represented with a series of pattern codes. The pattern of a voxel informs of the local shape of the model around that voxel. PCR can achieve a coding gain, since the pattern codes are highly correlated. In the multi-resolution framework, the coding gain can be further improved by exploiting the decimation constraints from the lower resolution models. Furthermore, the shell classification scheme is proposed to reduce the number of pattern codes to represent the whole voxel model. Simulation results show that the proposed algorithm provides about 1.1-1.3 times higher coding gain than the conventional PCR algorithm.

This paper presents an asynchronous data transfer scheme using 2-color 2-phase dual-rail encoding based on a differential operation and its circuit realization. The proposed encoding enables seamless asynchronous data transfer without inserting a spacer, because each logic value is represented by two kinds of codewords with dual-rail, called "color" data. Since the difference x-x between components of a codeword (x,x) becomes constant in every valid state, the data-arrival state can be detected by calculating the difference x-x. From the viewpoint of circuit implementation, during the state transition, since the dual-rail x and x are defined so as to transit differentially, the compatibility with a comparator using a differential amplifier becomes high, which results in reduction of the cycle time. It is evaluated using HSPICE simulation with a 0.18 µm CMOS technology that communication speed using the proposed dual-rail encoding becomes 1.4 times faster than that using conventional dual-rail encoding.

Energy consumption is one of the most critical constraints in the design of portable embedded systems. This paper describes an empirical study about the impacts of compiler optimizations on the energy consumption of the address bus between processor and instruction memory. Experiments using a number of real-world applications are presented, and the results show that transitions on the instruction address bus can be significantly reduced (by 85% on the average) by the compiler optimizations together with bus encoding.