Algorithm Process of Digital Beamforming with Implementation Details

This program provides a comprehensive description of the digital beamforming algorithm process, featuring detailed technical explanations and code-related implementation approaches for signal processing and beam steering operations.

MATLAB Code Implementation for Beamforming with Algorithm Details

This MATLAB program demonstrates beamforming algorithms, providing insights into the implementation process, key functions, and scientific principles behind signal directionality enhancement in wireless communications.

Artificial Immune System

Algorithm Process: 1. Parameter Configuration Random generation of initial population - population = initpop(popsize, chromlength) Fault type encoding, each row represents: code(1,:) for normal; code(2,:) for 50%; code(3,:) for 1.5%. Actual fault measurement data encoding, referred to as Unnormalcode, 188% 4. Iteration Initialization (M): 1) Calculate objective function value: Euclidean distance [objvalue] = calobjvalue(population, i) 2) Calculate fitness value for each individual in population: fitvalue = calfitvalue(objvalue)