In this paper, we present a new approach which is spanning tree-based genetic algorithm for solving a multi-objective transportation problem. The transportation problem as a special type of the network optimization problems has the special data structure in solution characterized as a transportation graph. In encoding transportation problem, we introduce one of node encodings based on a spanning tree which is adopted as it is capable of equally and uniquely representing all possible basic solutions. The crossover and mutation were designed based on this encoding. Also we designed the criterion that chromosome has always feasibility converted to a transportation tree. In the evolutionary process, the mixed strategy with (µ+λ)-selection and roulette wheel selection is used. Numerical experiments show the effectiveness and efficiency of the proposed algorithm.

In this paper, an effective method of system modeling and dynamic scheduling to improve operation and control for the Back-End process of semiconductor manufacturing is developed by using Colored Timed Petri-Nets (CTPNs). The simulator of a CTPNs model was utilized to generate a new heuristic scheduling method with genetic algorithm(GA) which enables us to obtain the optimal values of the weighted delay time and standard deviation of lead time.

Given a Petri net PN=(P, T, E), a siphon is a set S of places such that the set of input transitions to S is included in the set of output transitions from S. Concerning extraction of minimal siphons containing a given specified set Q of places, the paper proposes three algorithms based on branch-and-bound method for enumerating, if any, all minimal siphons containing Q, as well as for extracting such one minimal siphon.

The constant modulus algorithm (CMA) of the adaptive array has been developed for suppressing the co-channel interference and the intersymbol interference in mobile communications. In this paper a novel CMA for the hybrid of the adaptive array and equalizer (HAE) is proposed to combat the problems of insufficient degrees of freedom and mainbeam multipath interferers. The HAE with CMA utilizes the constant modulus property for the output signal of the HAE to adjust the weight vectors of the array and equalizer simultaneously. The co-channel interferers can be canceled by the array and the multipath interferers can be removed by the array or the equalizer following the array in the HAE. Therefore, the array in the HAE with CMA may need less number of elements than that required by the CMA array which cancels both the co-channel interferers and multipath interferers. Besides, the presence of the mainbeam multipath interferers, which may seriously degrade the performance of the CMA array, has much less effect on the HAE with CMA since it can be suppressed by the equalizer instead of the array. Simulation results are presented to demonstrate the merits of the CMA for the HAE.

The design of high performance-circuits using Field-Programmable Gate Arrays (FPGAs) requires a balance between the FPGA's architecture and CAD algorithms. Conventional FPGAs and CAD algorithms are developed independently, which makes it difficult to implement application circuits. To solve this problem, we developed a CAD-verified FPGA whose architecture was designed at the same time as the CAD algorithms. This paper shows how a CAD-verified FPGA architecture can simplify a routing algorithm. The algorithm is studied in terms of computational complexity and is simplified using the properties of our FPGA (switch module structure and the number of routing resources). The routing algorithm is almost one hundred times faster than that of the conventional router, and the quality of its circuits is also improved.

This paper deals with two-processor scheduling for a class of program nets, that are acyclic and SWITCH-less, and of which each node has unity node firing time. Firstly, we introduce a hybrid priority list L* that generates optimal schedules for the nets whose AND-nodes possess at most single input edge. Then we extend L* to suit for general program nets to give a new priority list L**. Finally, we use genetic algorithm to do the performance evaluation for the schedules generated by L** and show these schedules are quite close to optimal ones.

Heterojunction bipolar transistors (HBTs) are key devices for a variety of applications including L-band power amplifiers, high speed A/D converters, broadband amplifiers, laser drivers, and low phase noise oscillators. AlGaAs emitter HBTs have demonstrated sufficient reliability for L-band mobile phone applications. For applications which require extended reliability performance at high junction temperatures (>250) and large current densities (>50 kA/cm2), InGaP emitter HBTs are the preferred devices. The excellent reliability of InGaP/GaAs HBTs has been confirmed at various laboratories. At a moderate current density and junction temperature, Jc = 25 kA/cm2 and Tj = 264, no device failures were reported out to 10,000 hours in a sample of 10 devices. Reliability testing performed up to a junction temperature of 360 and at a higher current density (Jc = 60 kA/cm2) showed an extrapolated MTTF of 5 105 hours at Tj = 150. The activation energy for AlGaAs/GaAs HBTs was 0.57 eV, while the activation energy for InGaP/GaAs HBTs was 0.68 eV, which indicated a similar failure mechanism for both devices.

In this paper, we study the link capacity assignment problem in packet-switched networks (CA problem) focusing on the case where link cost function is a piecewise linear concave function. This type of cost function arises in many communication network design problems such as those arising from developments in communication transmission technologies. It is already known that the method of link set assignment is applicable for solving the CA problem with piecewise linear convex cost function. That is, each link in the network is assigned to one of a group of specific sets, and checked for link set contradiction. By extending the method of link set assignment to the case of piecewise linear concave cost function, an important characteristic of the optimal solution of the CA problem is derived. Based on this characteristic, the non-differentiable link cost function can be treated as a differentiable function, and a heuristic algorithm derived from the Lagrange multiplier method is then proposed. Although it is difficult to determine the global optimum of the CA problem due to its non-convexity, it is shown by numerical results that the solution obtained from the proposed algorithm is very close to the global optimum. Moreover, the computation time is linearly dependent on the number of links in the problem. These performances show that the proposed algorithm is very efficient in solving the CA problem, even in the case of large-scale networks.

With the knowledge of the syndromes Sa,b, 0a,b q-2, the exact error values cannot be determined by using the conventional (q-1)2-point discrete Fourier transform in the decoding of a plane algebraic-geometric code over GF(q). In this letter, the inverse q-point 1-dimensional and q2-point 2-dimensional affine Fourier transform over GF(q) are presented to be used to retrieve the actual error values, but it requires much computation efforts. For saving computation complexity, a modification of the affine Fourier transform is derived by using the property of the rational points of the plane Hermitian curve. The modified transform, which has almost the same computation complexity of the conventional discrete Fourier transform, requires the knowledge of syndromes Sa,b, 0 a,b q-2, and three more extended syndromes Sq-1,q-1, S0,q-1, Sq-1,0.

The minimum mean-squared error (MMSE) linear detector has been proposed to successfully suppress the multiple access interference and mitigate the near-far problem in direct-sequence code-division multiple access communication systems. In the presence of unknown or time-varying channel parameters, the MMSE linear detector can be implemented by the blind Griffiths' algorithm, which uses the desired signal vector instead of a training sequence of symbols for initial adaptation. In this paper, a variable step-size (VSS) Griffiths' algorithm is proposed for accelerating the convergence speed, especially in the presence of strong interference. Numerical results show that the convergence properties of the VSS Griffiths' algorithm are robust against the wide eigenvalue-spread problem of the correlation matrix associated with the received signal vector compared to the Griffiths' algorithm using a fixed step-size.

A unified algorithm is presented for solving key equations for decoding alternant codes. The algorithm can be applied to various decoding techniques, including bounded distance decoding, generalized minimum distance decoding, Chase decoding, etc.

This paper addresses the problem of learning Bayesian belief networks (BBN) based on the minimum description length (MDL) principle. First, we give a formula of description length based on which the MDL-based procedure learns a BBN. Secondly, we point out that the difference between the MDL-based and Cooper and Herskovits procedures is essentially in the priors rather than in the approaches (MDL and Bayesian), and recommend a class of priors from which the formula is obtained. Finally, we show as a merit of using the formula that a modified version of the Chow and Liu algorithm is obtained. The modified algorithm finds a set of trees rather than a spanning tree based on the MDL principle.

Tail-biting trellises of linear and nonlinear block codes are addressed. We refine the information-theoretic approach of a previous work on conventional trellis representation, and show that the same ideas carry over to tail-biting trellises. We present lower bounds on the state and branch complexity profiles of these representations. These bounds are expressed in terms of mutual information between different portions of the code, and they introduce the notions of superstates and superbranches. For linear block codes, our bounds imply that the total number of superstates, and respectively superbranches, of a tail-biting trellis of the code cannot be smaller than the total number of states, and respectively branches, of the corresponding minimal conventional trellis, though the total number of states and branches of a tail-biting trellis is usually smaller than that of the conventional trellis. We also develop some improved lower bounds on the state complexity of a tail-biting trellis for two classes of codes: the first-order Reed-Muller codes and cyclic codes. We show that the superstates and superbranches determine the Viterbi decoding complexity of a tail-biting trellis. Thus, the computational complexity of the maximum-likelihood decoding of linear block codes on a tail-biting trellis, using the Viterbi algorithm, is not smaller than that of the conventional trellis of the code. However, tail-biting trellises are beneficial for suboptimal and iterative decoding techniques.

In this paper, we state some noteworthy facts in connection with simplification of the BCJR algorithm using the bidirectional Viterbi algorithm (BIVA). That is, we clarify the necessity of metric correction in the case that the BIVA is applied to reliability estimation, where information symbols uj obey non-uniform probability distributions.

In this paper, we present simulation algorithms among enhanced mesh models. The enhanced mesh models here include reconfigurable mesh and mesh with multiple broadcasting. A reconfigurable mesh (RM) is a processor array that consists of processors arranged to a 2-dimensional grid with a reconfigurable bus system. The bus system can be used to dynamically obtain various interconnection patterns among the processors during the execution of programs. A horizontal-vertical RM (HV-RM) is obtained from the general RM model, by restricting the network topology it can take to the ones in which each bus segment must be along row or column. A mesh with multiple broadcasting (MWMB) is an enhanced mesh, which has additional broadcasting buses endowed to every row and column. We present two algorithms:1) an algorithm that simulates a HV-RM of size nn time-optimally in θ(n) time on a MWMB of size nn, and 2) an algorithm that simulates a RM of size nn in θ(log2 n) time on a HV-RM of size nn. Both algorithms use a constant number of storage in each processor. Furthermore, we show that a RM of size nn can be simulated in θ((n/m)2 log n log m) time on a HV-RM of size mm, in θ ((n/m)2 m log n log m) time on a MWMB of size mm (m < n). These simulations use θ((n/m)2) storage in each processor, which is optimal.

In 1995, 8 kb/s CS-ACELP coder of G.729 is standardized by ITU-T SG15 and it has been reported that the speech quality of G.729 is better than or equal to that of 32 kb/s ADPCM (G.726). However G.729 is the fixed rate speech coder, and it does not consider the property of voice activity in mutual conversation. If we use the voice activity, we can reduce the average bit rate in half without any degradations of the speech quality. In this paper, we propose an efficient variable rate algorithm for G.729. The variable rate algorithm consists of two main subjects, the rate determination algorithm and the design of sub rate coders. For the robust VAD algorithm, we combine the energy-thresholding method, the phonetic segmentation method by integration of various feature parameters obtained through the analysis procedure, and the variable hangover period method. Through the analysis of noise features, the 1 kb/s sub rate coder is designed for coding the background noise signal. Also, we design the 4 kb/s sub rate coder for the unvoiced parts. The performance of the variable rate algorithm is evaluated by the comparison of speech quality and average bit rate with G.729. Subjective quality test is also done by MOS test. Conclusively, it is verified that the proposed variable rate CS-ACELP coder produces the same speech quality as G.729, at the average bit rate of 4.4 kb/s.

We study some sufficient conditions of codeword lengths for the existence of a fix-free code. Ahlswede et al. proposed the 3/4 conjecture that Σi=1n a-li 3/4 implies the existence of a fix-free code with lengths li when a=2 i. e. the alphabet is binary. We propose a more general conjecture, and prove that the upper bound of our conjecture is not greater than 3/4 for any finite alphabet. Moreover, we show that for any a2 our conjecture is true if codeword lengths l1,l2,. . . consist of only two kinds of lengths.

Systolic array implementations of modified Gaussian eliminations for the decoding of an (n, n-2t) RS code, including the Hong-Vetterli algorithm and the FIA proposed by Feng and Tzeng, are designed in this paper. These modified Gaussian eliminations are more easily understanding than the classical Berlekamp-Massey algorithm and, in addition, are efficient to decode RS codes for small e or e <

This paper shows the design of multi-stage fuzzy inference system with smaller number of rules based upon the optimization of rules by using the genetic algorithm. Since the number of rules of fuzzy inference system increases exponentially in proportion to the number of input variables powered by the number of membership function, it is preferred to divide the inference system into several stages (multi-stage fuzzy inference system) and decrease the number of rules compared to the single stage system. In each stage of inference only a portion of input variables are used as the input, and the output of the stage is treated as an input to the next stage. If we use the simplified inference scheme and assume the shape of membership function is given, the same backpropagation algorithm is available to optimize the weight of each rule as is usually used in the single stage inference system. On the other hand, the shape of the membership function is optimized by using the GA (genetic algorithm) where the characteristics of the membership function is represented as a set of string to which the crossover and mutation operation is applied. By combining the backpropagation algorithm and the GA, we have a comprehensive optimization scheme of learning for the multi-stage fuzzy inference system. The inference system is applied to the automatic bond rating based upon the financial ratios obtained from the financial statement by using the prescribed evaluation of rating published by the rating institution. As a result, we have similar performance of the multi-stage fuzzy inference system as the single stage system with remarkably smaller number of rules.

When we have a singular Cab curve with many rational points, we had better to construct linear codes on its normalization rather than the original curve. The only obstacle to construct linear codes on the normalization is finding a basis of L( Q) having pairwise distinct pole orders at Q, where Q is the unique place of the Cab curve at infinity. We present an algorithm finding such a basis from defining equations of the normalization of the original Cab curve.