Читать книгу Handbook of Intelligent Computing and Optimization for Sustainable Development - Группа авторов - Страница 49

The researchers further designed the algorithm of linear perceptron categorizer in the context of DNA computation. The steps of the algorithm are given below.

 • The input vector, X(k) = (x1, x2, …, xn), is represented by n DNA strands which are extracted from sample molecular library.If the input value of ith neuron = 0 (where i = 1, 2, …, n), then the coding mode is denoted byIf the input value of ith neuron = 1, then the coding mode is denoted byThe value of additional bias signal is always 1. Thus, the coding mode of bias signal isIn the molecular library, there are 2n + 1 types of DNA strands each of which are five bases long.Again, the output values are also represented by five bases long DNA strands. If the output value of jth neuron = 0 (where j = 1, 2, …, m), then the coding mode is denoted byIf the input value of jth neuron = 1, then the coding mode is denoted by

 • These strands are hybridized with the DNA library representing weight coefficient.

 • DNA strands are made representing the set of weights denoted by w1, w2, …, wp.

 • The DNA strands representing the weight coefficient wij have four domains. The coding modes are presented by the following expression:(2.9)wherethe first domain takes in input value of ith input neuron;the second domain wij which is fifteen bases long represents weight coefficient;the third domain vij represents the arithmetic of input value and wij; the length of this domain is proportional to its true value, but not less than five bases;the fourth domain represents the weight coefficient wi=1,j which joins (i+1)th input neuron and jth output neuron.There are four special weights are represented by the expressions illustrated below:(2.10)(2.11)(2.12)(2.13)

 • Intersection can be calculated by performing gel electrophoresis using the DNA strands w1, w2,…, wp and w is derived.

 • Classification of unknown input vector can be derived from DNA strands representing the weight set w.