MATLAB Code Implementation for Random Sequence Generation

In this paper, we present several distinct programs including implementations for random sequence generation, white noise generation algorithms, and M-sequence generation techniques. Additionally, we discuss various least squares identification programs that facilitate better understanding of practical pressure system operations. These identification programs encompass batch processing implementations for second-order systems, recursive algorithms for sequential data processing, and augmented approaches that extend standard least squares methods. Through the application of these programs, researchers can effectively analyze and comprehend the performance characteristics of practical pressure systems while generating valuable insights and methodologies for future research endeavors. The implementations typically involve MATLAB's random number generation functions (rand, randn), sequence manipulation techniques, and matrix operations for solving least squares problems efficiently using built-in functions like lscov or manual implementation of normal equations.