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computingBERConvolutionalCod1

于 2010-07-13 发布文件大小:5KB

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Script for computing BER with Binary Convolutional Code and Viterbi decoding with finite survivor state memory and variable traceback depth Convolutional code of Rate-1/2, Generator polynomial - [7,5] octal Hard decision decoding is used.

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Script for computing BER with Binary Convolutional Cod1.doc,41472,2010-07-13

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moyituhuo
模拟退火算法的基本思想是从一给定解开始,从邻域中随机产生另一个解,接受Metropolis准则允许目标函数在有限范围内变坏,它由一控制参数t决定,其作用类似于物理过程中的温度T,对于控制参数的每一取值,算法持续进行“产生—判断—接受或舍去”的迭代过程,对应着固体在某一恒定温度下的趋于热平衡的过程,当控制参数逐渐减小并趋于0时,系统越来越趋于平衡态,最后系统状态对应于优化问题的全局最优解,该过程也称为冷却过程,由于固体退火必须缓慢降温,才能使固体在每一温度下都达到热平衡,最终趋于平衡状态,因此控制参数t经缓慢衰减,才能确保模拟退火算法最终优化问题的整体最优解。(Simulated annealing algorithm based on the idea that a given solution from the beginning, randomly generated from the adjacent domain to another solution, Metropolis acceptance criteria for the objective function to allow a limited range of deterioration, which is a control parameter t decided that its role is similar to the physical the course of the temperature T, the control parameters for each value, the algorithm continued to "have- to determine- to accept or rounding" of the iterative process, corresponding to a solid at a constant temperature of the process tends to thermal equilibrium, when control parameters and tended to decrease gradually 0:00, the system equilibrium state more and more, and finally the system state corresponds to the optimization problem of global optimal solution, the process is also known as the cooling process must be slow as a result of annealing temperature of solid to make solid temperature in each of them had attained thermal equilibrium, and ultim)

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computingBERConvolutionalCod1

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