Linear Convolution Linear convolution is a mathematical operation done to calculate the output of any Linear-Time Invariant (LTI) system given its input and impulse response. It is applicable for both continuous and discrete-time signals. We can represent Linear Convolution as y(n)=x(n)*h(n) Here, y(n) is the output (also known as convolution sum). x(n) is the input signal, and h(n) is the impulse response of the LTI system. In linear convolution, both the sequences (input and impulse response) may or may not be of equal sizes. That is, they may or may not have the same number of samples. Thus the output, too, may or may not have the same number of samples as any of the inputs. For example:- consider the following signals x(n): [1,2,3] h(n): [1,2,3,4,5] As you can see, the number of samples in the input and Impulse response signals is not the same. Still, linear convolution is possible. Here’s how you calculate the number of samples in the output of linear convolu...

  Introduction Of Signals And Systems Digital Signal Processing Digital In digital communication, we use discrete signals to represent data using binary numbers. Signal A signal is anything that carries some information. It’s a physical quantity that conveys data and varies with time, space, or any other independent variable. It can be in the time/frequency domain. It can be one-dimensional or two-dimensional. Processing The performing of operations on any data in accordance with some protocol or instruction is known as processing. System A system is a physical entity that is responsible for the processing. It has the necessary hardware to perform the required arithmetic or logical operations on a signal.    Digital Signal Processing Digital Signal Processing is the process of representing signals in a discrete mathematical sequence of numbers and analyzing, modifying, and extracting the information contained in the signal by carrying out algorithmic operations and proces...

  Systems Systems process input signals to produce output signals A system is combination of elements that manipulates one or more signals to accomplish a function and produces some output.  Classification Of Systems The systems are classified as Static & dynamic system Time invariant and variant system Linear and non linear system Causal and non causal system Stable and unstable system Static and dynamic system Static system is said to be a memoryless system. The output does not depend the past or future input. It only depends the present input for an output. Ex:- y(n) = x(n) Dynamic system is said to be as system with memory. Its output depend the past values of input for an output. Ex:- Y(n) = x(n) + x(n - 1) This static and dynamic systems are otherwise called as memoryless and system with memory. Systems with and without memory A system is called memory less if the output at any time t (or n) depends only on the input at time t (or n); in other words, independent of t...

  Analog To Digital Conversion An analog-to-digital converter (abbreviated ADC, A/D or A to D) is a device that converts a continuous quantity to a discrete digital number. Or A device that converts continuously varying analog signals from instruments and sensors that monitor conditions, such as sound, movement and temperature into binary code for the computer. The A/D converter may be contained on a single chip or can be one circuit within a chip. Analog to Digital Converter (ADC) is an electronic integrated circuit used to convert the analog signals such as voltages to digital or binary form consisting of 1s and 0s. Most of the ADCs take a voltage input as 0 to 10V, -5V to +5V, etc., and correspondingly produces digital output as some sort of a binary number. Analog : continuously valued signal, such as temperature or speed, with infinite possible values in between  Digital : discretely valued signal, such as integers, encoded in binary  Analog-to-digital converter: ADC...