In order to improve the ability of software dynamic image fault detection, a software dynamic image fault recovery path detection algorithm based on a fuzzy control algorithm is proposed. A software dynamic image fault signal model of a software dynamic image fault was constructed by adopting an embedded feature extraction and a fuzzy control algorithm, and the dynamic image fault signal of the embedded software under the multi-load was subjected to frequency spectrum decomposition and blind source separation. The method comprises the following steps: (1) carrying out noise reduction processing on a software dynamic image fault signal by adopting a multi-dimensional wavelet decomposition method, (2) carrying out wavelet entropy feature extraction on the software dynamic image fault signal of the noise reduction output, and (3) combining the wavelet structural feature recombination method to carry out the recombination of the software dynamic image fault feature. The high-order spectral characteristic of the software dynamic image fault signal was extracted and the high-order spectral characteristic of the extracted embedded software dynamic image fault recovery path was automatically matched, and the automatic identification and detection of the fault part of the software dynamic image was realized.

中文翻译：

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基于模糊控制算法的软件动态图像故障恢复路径分析

为提高软件动态图像故障检测能力，提出一种基于模糊控制算法的软件动态图像故障恢复路径检测算法。采用嵌入式特征提取和模糊控制算法构建软件动态图像故障的软件动态图像故障信号模型，对多负载下嵌入式软件的动态图像故障信号进行频谱分解和盲法。源头分离。该方法包括以下步骤：(1)采用多维小波分解方法对软件动态图像故障信号进行降噪处理，(2)对软件动态图像故障信号进行小波熵特征提取。降噪输出，(3)结合小波结构特征重组方法对软件动态图像故障特征进行重组。提取软件动态图像故障信号的高阶频谱特征并自动匹配提取的嵌入式软件动态图像故障恢复路径的高阶频谱特征，自动识别和检测软件动态故障部分形象实现了。