基于一位标识的测试向量混合编码压缩方法

Hybrid coding compression method of test vector based on an identification

提出了一种基于一位标识的测试向量混合编码压缩方法。本方法根据各个向量含X位的概率,把整个测试集分成两组,一组采用混合编码;另一组采用双游程编码。在混合编码中,整个测试数据被划分成若干个数据块。每个数据块又包含两个子数据块,第一个子数据块采用单游程编码,第二个子数据块采用一位标识法。解压时,以第一个子数据块的长度来计算出第二个子数据块的长度。这样,减少了一部分需要编码的数据。实验结果表明:该方法平均压缩率可达到68.74%,与其他方法相比可高出11.53%。

A hybrid coding compression method of test vector based on an identification is presented in this paper. According to the probability of vector containing X-bit, the entire test set is divided into two groups, a group of mixed coding, another group with double run-length coding. In hybrid coding, the entire test data is divided into a plurality of data block. Each data block contains two sub-data blocks, the first sub-block of data uses a single runlength coding, and the second sub-block of data uses an identification method. When the decompression, according to the length of first sub-data block, the length of the second sub-data block could be calculated. Thus, it can reduce the part data needing to be encoded. The experimental results show that this scheme can achieve better compression.