A Comparative Analysis and Application of the Compression Properties of Two 7-Bit Subsets of Unicode

Data compression is important in the computing process because it helps to reduce the space occupied by a file, which normally leads to the reduction in the time taken to access the file. Files which may be compressed include text, images, video/speech and sound. Data compression algorithms have been developed and applied to several areas including neural networks, bioinformatics, database management systems, wireless systems, error detection and correction codes, fractals etc. Since computer/communication codes are binary texts, they may be compressed using binary text compression algorithms. By considering two binary texts which can be modeled as subsets of Unicode, namely the numerics of a 7-bit subset of the Inf or mation Processing Code (IPC) and the numerics of the 7-bit American Standard Code for Information Interchange (ASCII) respectively, this paper presents a comparative analysis of the compression properties of these two texts using a binary text compression algorithm. The algorithm is a generalization of a storage-based built-in test pattern generation method for reducing storage requirements and test application time in circuits. This algorithm is then applied to the design of an IPC to ASCII code converter. Code converters are circuits which accept input codes in one form and translate them to present equivalent values in a different format as the output code. They are useful in real-time control systems and data acquisition systems, such as aviation systems and patient-monitoring systems in hospitals, which require the use of different sensors to continuously monitor the computer. This paper thus presents an equivalent approach to the design of code converters via the well-known k-map method.