Filter Design Using Window Method
Designing High-Pass, Low-Pass, and Band-Pass Filters with Window Functions
Digital Bandpass Filter Design using Chebyshev Method
Digital filters are computational systems that process digital signals to modify frequency components by altering their relative proportions or eliminating specific frequencies. Classic digital filters are categorized by their frequency response characteristics into low-pass, high-pass, band-pass, and band-stop types. The magnitude response illustrates amplitude attenuation across frequencies, while the phase response indicates time delays introduced by the filter. This course project introduces Chebyshev digital bandpass filter theory and implements a design using MATLAB's buttord and butter functions to analyze performance metrics through loss function and phase response visualizations.
Designing Low-Pass, Band-Pass, and High-Pass Filters Using Kaiser Window
This MATLAB function implements Kaiser window-based design for low-pass, band-pass, and high-pass filters with unified graphical display. The package includes required impulse functions and impulse response functions, operating with digital frequency values. The implementation allows parameter adjustment for optimal filtering performance, including window length and cutoff frequency configuration.
Ideal Filter Implementation for Low-Pass and Band-Pass Filtering
% y = filter(sig, fmin, fmax, fs) % Performs ideal filtering on a signal to achieve low-pass or band-pass filtering functionality % sig: input signal to be filtered % fmin: lower cutoff frequency (when fmin=0, implements low-pass filter; when fmin>0, implements band-pass filter) % fmax: upper cutoff frequency (must satisfy fmax > fmin) % fs: sampling frequency of the input signal % y: filtered output signal
MATLAB Code Implementation for GUI-Based Speech Signal Filtering Application
A comprehensive GUI application for speech signal processing featuring low-pass, band-pass, multi-band-pass filtering implementations using FFT convolution algorithms with MATLAB code integration.
IIR Filter Design Using Bilinear Transformation Method
Computer program for designing lowpass, bandpass, and highpass IIR digital filters using the bilinear transformation design methodology, featuring implementation of critical filter design algorithms and parameter configuration functions.
MATLAB Programming Implementation of Butterworth Low-Pass and Band-Pass Filters
Implementing Butterworth low-pass and band-pass filters using MATLAB programming with signal processing applications
FIR Filter Design and Implementation with Code Examples
Implementing FIR filter design with practical examples including bandpass and low-pass filters, complete with MATLAB code demonstrations and comprehensive result analysis discussing filter performance characteristics and applications.
Filters and Pseudocolor Transformation
A comprehensive implementation featuring: 1. Universal functions for high-pass, low-pass, band-pass, and band-stop filtering 2. Multiple filter types including Ideal, Butterworth, and Exponential implementations 3. Pseudocolor processing with included design documentation and algorithm explanations.
Low-pass, Band-pass, High-pass, and Band-stop FIR Digital Filters
Designing Low-pass, Band-pass, High-pass, and Band-stop FIR Digital Filters Using MATLAB with Low-pass Sampling