Real Number Coding Research Articles

Slotting Optimization Algorithm of the Stereo Warehouse

In order to solve the problem of slotting optimization management with automated storage and retrieval system (AS / RS), the genetic algorithms of the slotting optimization process with stereo warehouse were discussed. The process of the slotting optimization was designed by the real-number coding. The mathematical models of the slotting optimization and cargo shipping time were built, and the simulation calculation of the models was done. The stability of the shelf and the efficiency of the accessing goods were significantly improved by the optimization simulation of the distribution of cargo space, after optimizing the storage order. The algorithms of the slotting optimization with stereo warehouse could effectively enhance the frequency of the stock in & out, increasing the revenue.

Hermitian Symmetric DFT Codes: A New Class of Complex DFT Codes

We introduce a new class of real number codes derived from DFT matrix, Hermitian symmetric DFT (HSDFT) codes. We propose a new decoding algorithm based on coding-theoretic as well as subspace based approach. Decoding of HSDFT codes requires only real arithmetic operations and smaller dimension matrices compared to the decoding of the state-of-art real BCH DFT (RBDFT) class of codes. HSDFT codes will also be shown to have more burst error correction capacity. For a Gauss-Markov source, on a binary symmetric channel at lower to moderate bit error rates (BERs), HSDFT codes show better performance than RBDFT codes, and on a Gilbert-Elliot channel HSDFT codes consistently perform better than RBDFT codes.

The System of Spindle Optimization Design Based on GA

Aiming at the optimization design of spindle, this paper introduces deflection constraint, strength constraint, corner constraint, cutting force constraint, the limit of torsional deflection, boundary constraint of design variable, dynamic property constraint , realizes the expression of the mathematical model of the spindle optimization design. Through the introduction of the real number code rule, the selection operator is built by adopting the optimum maintaining tactics and proportional selection, the crossover operator is built by using the method of arithmetic crossover and the mutation operator is built by using the method of uniform mutation. In the platform of VC++, the system of spindle optimization design based on GA is built. The analysis of the example shows that using the genetic algorithm to optimize the spindle can ensure the convergence of the optimization course, expand the search space, and the effect of optimization is obvious.

Optimal control strategy for energy saving in trains under the four-aspect fixed autoblock system

This paper deals with both the leading train and the following train in a train tracking under a four-aspect fixed autoblock system in order to study the optimum operating strategy for energy saving. After analyzing the working principle of the four-aspect fixed autoblock system, an energy-saving control model is created based on the dynamics equation of the trains. In addition to safety, energy consumption and time error are the main concerns of the model. Based on this model, dynamic speed constraints of the following train are proposed, defined by the leading train dynamically. At the same time, the static speed constraints defined by the line conditions are also taken into account. The parallel genetic algorithm is used to search the optimum operating strategy. In order to simplify the solving process, the external punishment function is adopted to transform this problem with constraints to the one without constraints. By using the real number coding and the strategy of dividing ramps into three parts, the convergence of GA is accelerated and the length of chromosomes is shortened. The simulation result from a four-aspect fixed autoblock system simulation platform shows that the method can reduce the energy consumption effectively in the premise of ensuring safety and punctuality.

The Application of Genetic Algorithm in Layout Design of Oil Rig Driller Console

In order to avoid the shortage of subjective judgment, carrying on the human-machine interface layout scientifically, this paper put forward that the genetic algorithm was applied to the layout design of oil rig driller console. Using real number coding, combining with human-machine interface layout principles to establish the mathematical model, genetic algorithm was adopted to optimize the layout. Developed an intelligent layout optimization system on basis of VB, and took the layout scheme formation process of the manipulators which on the right hand area of driller console as an example to explain the system. Theory and example analysis showed that the algorithm could generate the layout scheme quickly and effectively, solved the problem that layout principles were difficult to be quantize in the traditional layout design and the quality of layout was hard to judge, and to a certain extent, has realized automatic layout.

Application of Genetic Algorithms in Particle Inversion

In the general light scattering particle size measurement methods, the inversion error of results is nonuniform distribution. To solve this problem, genetic algorithms based on real number coding were proposed to be applied in the inversion of particle size distribution. In this method, the fitness function was further improved in order to reduce the individual error, it not only considered sum of all errors but also took into account the individual maximum error. With this improved fitness function, the error distribution is homogenized. The light spectrum about measurement and calculation are basic entirely fitting. The results show that the algorithm is accurate and reliable.

Checksum-Based Probabilistic Transient-Error Compensation for Linear Digital Systems

In this paper, a probabilistic compensation technique for minimizing the effect of transient errors effect is proposed. The focus is to develop a compensation technique for DSP applications in which exact error compensation is not necessary and end-to-end system level performance is degraded minimally as long as the impact of the ldquonoiserdquo injected into the system by the transient errors is minimized. The proposed technique, called checksum-based probabilistic compensation, uses real-number checksum codes for error detection and partial compensation. Traditional coding techniques need a code of distance three and relatively complex calculations for perfect error correction. Here, it is shown that a distance-two code can be used to perform probabilistic error compensation in linear systems with the objective of improving the signal-to-noise ratio in the presence of random transient errors. The goal is to have a technique with small power and area overhead and to perform compensation in real time with negligible latency. The proposed technique is comprehensive and can handle errors in the combinational circuitry and storage elements. Comparison against a system with no error correction shows that up to 13-dB SNR improvement is possible. The area, power, and timing overheads of the proposed technique are analyzed.

Stable DFT codes and frames

Discrete Fourier transform codes (DFT codes) or real number codes have been studied and recognized as useful (as joint source-channel codes, for example) but are not stable under bursty losses. This paper introduces a two-channel DFT code with an interleaver and shows that its numerical stability far exceeds that of the corresponding single-channel DFT code (the ratio of the frame bounds for the two-channel system can be smaller by many orders of magnitude). This leads to a stable way of dealing with bursts of errors using DFT codes.

A new evolutionary algorithm based on the decimal coding

Traditional Evolutionary Algorithm (EAs) is based on the binary code, real number code, structure code and so on. But these coding strategies have their own advantages and disadvantages for the optimization of functions. In this paper a new Decimal Coding Strategy (DCS), which is convenient for space division and alterable precision, was proposed, and the theory analysis of its implicit parallelism and convergence was also discussed. We also redesign several genetic operators for the decimal code. In order to utilize the historial information of the existing individuals in the process of evolution and avoid repeated exploring, the strategies of space shrinking and precision alterable, are adopted. Finally, the evolutionary algorithm based on decimal coding (DCEAs) was applied to the optimization of functions, the optimization of parameter, mixed-integer nonlinear programming. Comparison with traditional GAs was made and the experimental results show that the performances of DCEAS are better than the tradition GAs.

On the complexity of bounded distance decoding for the AWGN channel

Earlier work has derived the storage complexity of the bounded distance decoder (BDD) for binary channel convolutional codes. We extend this work to the Gaussian noise channel and to partial-response codes. We show that the storage requirement /spl sim/(2/sup 1-R/ - 1)/sup -t/ paths for rate-R convolutional codes over the binary channel becomes /spl sim/2/sup 2Rt/ over the Gaussian channel, where the decoder must correct t errors. Thus, convolutional coding over the Gaussian channel is not only 3 dB more energy efficient, but its decoding is simpler as well. Next, we estimate the path storage for partial-response codes, i.e., real-number convolutional codes, over the Gaussian channel. The growth rate depends primarily on the bandwidth of the code. A new optimization procedure is devised to measure the maximum storage requirement in Gaussian noise for these two code types. An analysis based on difference equations predicts the asymptotic storage growth for partial response codes.

Resolution of Overlapping Chromatographic Peaks Using a Genetic Algorithm

ABSTRACT A genetic algorithm for resolution of overlapping chromatographic peaks (GAROCP) using real-number coding, non-uniform mutation and arithmetical crossover methods is described in this paper. It was applied to resolution of highly overlapped multicomponent high-performance liquid chromatographic peaks by fitting experimental chromatogram to the exponentially modified Gaussian (EMG) model. The genetic algorithm was used to find the minimum of fitting error to optimize the parameters in the EMG functions which determine the shape and area of each peak. The applicability of the method was investigated with both simulated signals calculated by EMG functions and experimental multicomponent overlapping chromatograms.

A Wavelet-Based Genetic Algorithm for Compression and De-Noising of Chromatograms

ABSTRACT A wavelet-based genetic algorithm using real-number coding and arithmetical crossover method in signal processing is described in this work. Due to the characteristic of the wavelet, an analytical signal can be represented by a finite linear combination of wavelet-based functions. Using a wavelet-based genetic algorithm to find the coefficients to such representation, an analytical signal can be reconstructed by the coefficients and the corresponding elementary function. Therefore the method can be used to compress and de-noise analytical signals because the insignificant information such as noise will not be reserved in the reconstructed signal. Both simulated signals and experimental multicomponent chromatograms are successfully compressed and de-noised with the proposed algorithm.

Class of majority decodable real-number codes

A majority decoding algorithm for a class of real-number codes is presented. Majority decoding has been a relatively simple and fast decoding technique for codes over finite fields. When applied to decode real-number codes, the robustness of the majority decoding to the presence of background noise, which is usually an annoying problem for existing decoding algorithms for real-number codes, is its most prominent property. The presented class of real-number codes has generator matrices similar to those of the binary Reed-Muller codes and is decoded by similar majority logic.

Reliability levels for fault-tolerant linear processing using real number error correction

Fault-tolerant linear processing systems using real number codes, as in algorithm-based fault tolerance methodologies, can be extended to include error correction for correcting intermittent errors in the processed output data. The reliability function for a protected system containing correction is considered under simple but realistic assumptions on the arrival of failures in both the normal processing and corrector subassemblies. An error-correcting procedure employing a real, convolutional code is described briefly, and a system diagram of a corrector subsystem containing self-checking comparators for detecting its internal failures is presented. Failures are modelled as arriving according to Poisson processes in both parts of the fault-tolerant system. Formulas for the reliability of the protected system are given and an efficient lower bound is developed. This bound depends only on broad details such as relative areas used in a VLSI design of the processing and corrector parts. Computational methods employing computer algebra packages are discussed, and some typical reliability curves for two configurations demonstrate the dramatic improvement which error correction introduces.

Real-number codes for fault-tolerant matrix operations on processor arrays

A generalization of existing real numer codes is proposed. It is proven that linearity is a necessary and sufficient condition for codes used for fault-tolerant matrix operations such as matrix addition, multiplication, transposition, and LU decomposition. It is also proven that for every linear code defined over a finite field, there exists a corresponding linear real-number code with similar error detecting capabilities. Encoding schemes are given for some of the example codes which fall under the general set of real-number codes. With the help of experiments, a rule is derived for the selection of a particular code for a given application. The performance overhead of fault tolerance schemes using the generalized encoding schemes is shown to be very low, and this is substantiated through simulation experiments. >