Window Function Method for Designing FIR Bandpass, Lowpass, and Highpass Filters

This experiment focuses on designing FIR bandpass, lowpass, and highpass filters using the window function method. By modifying parameters in the program implementation, users can create custom filters with specific frequency response characteristics to address various signal processing needs. The window function method is a widely-used filter design technique that employs different window functions (such as Hamming, Hanning, or Blackman windows) to achieve desired frequency response properties. The implementation typically involves defining key parameters including filter order, cutoff frequencies, and window type selection. The core algorithm calculates the ideal filter coefficients first, then applies the chosen window function to truncate the infinite impulse response. Through parameter adjustment in the code, users can optimize filter performance characteristics like transition bandwidth and stopband attenuation. This flexible methodology finds applications across multiple signal processing domains including audio processing, image enhancement, and communication systems. The code structure generally includes functions for parameter input, coefficient calculation using mathematical convolution operations, and frequency response visualization through FFT analysis.