生物多感觉信号变异检测方法研究与仿真

动物不同脑部感官信息在频率、振幅等属性上差异较大,多个差异性较强的单感觉信息进行融合时会发生信号排异冲突,造成转化生成的脑部衰退特征信号强度较弱。提出了一种基于人工免疫算法的生物多感觉信号变异检测方法。建立信号变异特征动态变化方程,获取信号变异特征变异的交叉点分布情况。更新信号变异特征数据库,在数据库中选取信号变异特征。克服了传统算法的弊端。实验证明,这种算法能够避免信号变异特征突变的缺陷,提高了信号变异检测的准确率。

Feeling More than Biological Variation Signal Detection Method Research and Simulation

Different animals brain sensory information in frequency,amplitude attribute differences on,more difference strong single sensory information fusion signal happens rejection conflict,cause transformation of the generation of brain recession characteristic signal strength is weak.Put forward based on artificial immune algorithm is more than the biological variation signal detection method feeling.Establish signal mutation characteristics dynamic change equation,get the signal mutation characteristics lies at the intersection of variation distribution.Updated signal mutation characteristics database,in the database selection signal variation characteristics.To overcome the disadvantages of the traditional algorithm.Experiments show that the algorithm can avoid signal mutation characteristics of mutations defects,improve the signal detection accuracy of variation.