Design and Investigation of CDMA Baseband Transceiver Based Fourier Signals for Different Channel Estimation Algorithms in SUI Channels

Code Division Multiple Access (CDMA) and Orthogonal Frequency Division Multiplexing (OFDM) and are the technology used in all third generation cellular communications networks, and it is a promising candidate for the definition of fourth generation standards. This paper refers to channel estimation based on time-domain channel statistics. Using a general model for Stanford University Interim SUI channels model, the aim of the paper is to find out the most suitable channel estimation algorithms for the existing CDMA and modified the bit error rate for this system. Starting with the analysis of channel estimation algorithms, we present the Minimum Mean Square Error (MMSE (and Least Square (LS (estimators and compromising between performances under different channel scenarios. The bit error rate for a 16-QAM system is presented by methods of Matlab simulation results. Keywords: CDMA, OFDM, MMSE, LS, SUI

An efficient of estimation stages for segmentation skin lesions based optimization algorithm

Modern dermatology distinguishes premature diagnosis for example an important part in reducing the death percentage and promising less aggressive treatment for patients. The classifications comprise various stages that must be selected suitably using the characteristics of the filter pointing to get a dependable analysis. The dermoscopic images hold challenges to be faced and overcome to enhance the automatic diagnosis of hazardous lesions. It is calculated to survey a different metaheuristic and evolutionary computing working for filter design systems. Approximately general computing techniques are observed to improve features of infect design method. Nevertheless, the median filter (MF) is normally multimodal with respect to the filter factors and so, reliable approaches that can provide optimal solutions are required. The design of MF depends on modern artificial swarm intelligence technique (MASIT) optimization algorithm which has proven to be more effective than other population-based algorithms to improve of estimation stages for segmentation skin lesions. A controlled artificial bee colony (ABC) algorithm is advanced for solving factors optimization problems and, also the physical-programming-depend on ABC way is applied to proposal median filter, and the outcomes are compared to another approaches