Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/278
Title: DNA Computing for Signal Matching
Authors: Sharma, Madhu
Supervisor: Chana, Inderveer
Singh, Amardeep
Keywords: DNA Fundamental;DNA Computing Software;DSP Basic;Bel Electrophoresis
Issue Date: 1-May-2007
Abstract: Electronic computers are only the latest in a long chain of human efforts to use the best technology available for performing computations. Ever since scientists discovered that conventional silicon-based computers have an upper limit in terms of speed, even electronic computers have their limitations: there is a limit to the amount of data they can store, and physical laws dictate the speed thresholds that will soon be reached. They have been searching for alternate media with which to solve computational problems. That search has led us, One of the most recent attempts to break down these barriers is to replace, once more, the tools for performing computations with biological ones instead of electrical one enter DNA computing DNA computing was grounded in reality at the end of 1994, when Len Adleman of USC announced that he had solved a small instance of a computationally intractable problem using a small vial of DNA. By representing information as sequences of bases in DNA molecules, Adleman showed how to use existing DNA-manipulation techniques to implement a simple, massively parallel random search .DNA computing solve hard computational problem. After adleman experiment, DNA computing apply on so many hard computational problem. Matching of digital signals is a fundamental problem that arises in many signal processing application. Signals matching problem is also considered as NP-complete problem. This work report apply new approach DNA computing on the matching of query signal into the stored signal. This work report proposes a method for signal matching. It include biological notation and proposes algorithm. I developed the software for simulating the proposed method. This report also discuss existing classical approach A Quick Search Method for Audio and Video Signals Based on Histogram Pruning. Calculate CPU time of proposed method.
URI: http://hdl.handle.net/123456789/278
Appears in Collections:Masters Theses@CSED

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