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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Desai, S.R. Prasad, R. |
| Copyright Year | 2013 |
| Description | Author affiliation: Electr. Eng. Dept., Indian Inst. of Technolgy Roorkee, Roorkee, India (Desai, S.R.; Prasad, R.) |
| Abstract | This paper utilizes the nature inspired genetic optimization technique implemented on a TMS320C54X fixed point Digital Signal Processor(DSP) to scale down a given large scale model. The optimization technique adopted here is popularly used to solve highly nonlinear optimization problems effectively. The concept behind is to explore and introduce the use of an evolutionary technique on DSP to optimize the numerator and denominator coefficients of the reduced order model. The simulations are entirely carried out on TMS320C54X DSP through the Code Composer Studio (CCS). This new approach protects the stability and also matches the steady state value of the reduced model. The results presented signify the efficacy of the said technique. |
| Sponsorship | IEEE Kerala Sect. |
| Starting Page | 1 |
| Ending Page | 6 |
| File Size | 467120 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781467351508 |
| e-ISBN | 9781467351492 |
| DOI | 10.1109/AICERA-ICMiCR.2013.6576027 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-06-04 |
| Publisher Place | India |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Genetic algorithm(GA) High Order Model(HOM) Sociology Reduced order model(ROM) Digital signal processing Code composer studio(CCS) Mathematical model Digital signal processor(DSP) Statistics Optimization Read only memory Genetic algorithms |
| Content Type | Text |
| Resource Type | Article |
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