Addition of noise to speech

MATLAB CODE: clc; close all; clear all; [Data,fs,nbits]=audioread('speechfilename.wav');  % input wav file Data=Data(:,1); NoiseData=Data+0.05*randn(size(Data));  %defining Noise data wavplay(NoiseData,fs); X=fft(Data);      %FFT of data file X=abs(X); subplot(2,1,1); plot(X); grid on; y=fft(NoiseData);   %FFT of noise in data Y=abs(Y); subplot(2,1,1); plot(Y); audiowrite(filename,Y,fs);    %filename= output file

Python Libraries for Machine Learning

Machine Learning is gaining popularity these days with the advent of self driving cars,face recognition,social robots like Sophia etc. Machine learning is the application of Artificial Intelligence which enables systems to learn on their own without being explicitly programmed. Python provides libraries that help in machine learning and deep learning. Python is simple and powerful... Continue Reading →

Python Flask Introduction

Today we will learn something really cool. Its a simple and famous library in Python called Flask. Flask is a web development micro framework for Python. Flask is called a micro framework because it does not require particular tools or libraries. First let us see how to install Flask. 1. We go to the Windows... Continue Reading →

Design of a 4th order digital Chebeyshev type-I filter that passes only the component of 800πt from the signal: x(t)= 2*sin (100πt) + 3*cos (800πt) + sin (1500πt)

MATLAB CODE: fs=3000; t=0:1/fs:1; x=2*sin(100*pi*t)+3*cos(800*pi*t)+sin(1500*pi*t); X=fft(x); n=0:1:length(X)-1; plot(n,abs(X)); figure; N=4; f1=300; f2=500; Wp1=2*f1/fs; Wp2=2*f2/fs; Wp=[Wp1 Wp2]; R=3; [b,a]=cheby1(N,R,Wp); zplane(b,a); freqz(b,a); y=filter(b,a,x); Y=fft(y); figure; RESULTs: Input Signal Frequency Components: Filtered Signal Frequency Components:

Design of a digital low pass Butterworth filter (IIR)

MATLAB CODE: PBE=400; %Pass band edge frequency= 400 Hz SBE=800; %Stop band edge frequency= 800 Hz Fs=2000; %Sampling frequency= 2000 Hz Wp=2*PBE/Fs; Ws=2*SBE/Fs; W=0:1/Fs:pi; Rs=30;    %Stop band attenuation= 30 dB Rp=0.4;  %Pass band attenuation= 0.40 dB [N,Wn]=buttord(Wp,Ws,Rp,Rs); [b,a]=butter(N,Wn); zplane(b,a); figure; [H,W]=freqz(b,a); freqz(b,a); figure; plot(W,20*log10(abs(H))); RESULTs: POLES and Zeroes in Z-plane

Operation on Images Part 1

The analysis and manipulation of a digital image is called image processing. Python is widely used for image processing applications to suit the need of the user. Let us see how image processing is done in Python.  We will use a library called Pillow. Let us first install Pillow. In the Search Bar type cmd.... Continue Reading →

Drawing using Turtle

Turtle Graphics is a learning environment for Python programming inspired by Logo which is like a board that lets you command a turtle to draw all over the board using certain commands. Let us import turtle and see how it works. The turtle shape is a triangle by default. Let us try changing it to... Continue Reading →

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