MATLAB Implementation of Fuzzy Logic Functions with Source Code

This package provides MATLAB source code implementation related to fuzzy logic functions, complete with simulation diagrams. Fuzzy logic functions represent mathematical tools in computer science specifically designed to process ambiguous or uncertain information. The core algorithm maps various inputs to fuzzy outputs through membership functions and rule-based inference systems, enabling computers to effectively handle complex real-world problems. The implementation showcases practical applications of this mathematical approach, where input data undergoes fuzzification processes using triangular or Gaussian membership functions. The code then applies fuzzy inference mechanisms (typically Mamdani or Sugeno methods) to generate output distributions, which are subsequently defuzzified using techniques like centroid calculation to produce clear simulation results. Notably, the fuzzy logic framework extends beyond computer science applications and finds widespread use in control engineering, artificial intelligence systems, and decision-making algorithms. The code structure includes key components such as membership function definitions, rule base establishment, inference engine operations, and defuzzification modules. Understanding the principles and implementation techniques of fuzzy logic functions holds significant importance for grasping evolving trends in computational intelligence and developing robust systems capable of handling real-world uncertainties.