A New DNA Encoding Technology with Application in Signal Processing of Mechanical Engineering Systems

Considering Cellular Automata and A New Kind of Science in Engineering Science

Quan-Fang Wang

Chinese University of Hong Kong

Cellular automata theory has been widely applied in a variety of fields, such as nature, science, technology, and business as well as the arts and music. Our work is to find the “DNA” of signal processing by constructing a DNA algorithm based on proper encoding techniques. From the accomplishments of the study, it is obvious that the encoding methodology is closely related to cellular automata.

With an ever-increasing demand for quality, signal processing is now a compulsory requirement in engineering fields. Literature survey shows that a large amount of research has been carried out and various methods have been developed: time domain, frequency domain, spatial domain, time-frequency domain, and wavelet transform methods. Each method clearly has advantages and limitations.  

By encoding output signals coming from a sensor to a “DNA signal”, the bio-informatics science can be applied to analyze the DNA signal on the DNA domain. On the other hand, the constructed binary-like word domain enables us to find the “genome” of signals using the proposed DNA architecture.    

The DNA algorithm for signal processing includes seven steps.
      Step 1.   Take time series data.  
      Step 2.   Extend the time series.
      Step 3.   Encode the time series to DNA strands.
      Step 4.   Bio-information analysis for DNA sequences.
      Step 5.   Generate catenated DNA sequences.  
      Step 6.   Generate twin shuffle language.  
      Step 7.   Search for features.

Furthermore, the application to mechanical engineering systems has been demonstrated. It is hoped that cellular automata will be sufficiently applied in engineering and industry.

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