Logistic map and wavelet transform based differential evolution

Optimization of Spreading Code Using Modified Differential Evolution for Wireless Communication

“…The modification of the initialization of population along with the mutation rate is done in [9] using logistic map and wavelet transformation in DE respectively which increases the convergence rate and accordingly, after which test is done on various benchmarks problems. Thereafter, the results are compared with the state of the art algorithms along with different real-time none linear engineering problems to obtain their performance.…”

“…In Fig. 1, two mutation schemes are used, DE/best /1/bin and DE/ rand /1/bin which is explained below correspondingly with the help of mathematical terms [9].…”

“…3. Binary bits are generated using the thresholding method (method 1) and integer to bit conversion method (method 2) [9]. Properties (Mono bit test, run-length test, computational time) of optimized generated bits are compared with the nonoptimized one [1] as shown in the Table as shown in section 5.…”

“…Literature reflects that DE shows high-quality performance in application with different optimization problems [8]. Also various enhance methods of DE by modifying its parameters show a very good performance comparing to different recent optimization techniques [9].…”

“…This paper shows a comparative study of two recent modified techniques of DE with the help of engineering design problems and application of that modified DE (considering the better one) in wireless communication to optimize logistic map based spreading code. In a comparative study of DE, modification of DE is done with the help of wavelet transform [9] and exponential scale factor. A comparative study of properties of both optimized and non-optimized spreading code is also discussed in this paper.…”