Design Technique of Bandpass FIR filter using Various Window Function

In signal processing, there are many instances in which an input signal to a system contains extra unnecessary content or additional noise which can degrade the quality of the desired portion. In such cases we may remove or filter out the useless samples. For example, in the case of the telephone system, there is no reason to transmit very high frequencies since most speech falls within the band of 400 to 3,400 Hz. Therefore, in this case, all frequencies above and below that band are filtered out. The frequency band between 400 and 3,400 Hz, which isn’t filtered out, is known as the pass band, and the frequency band that is blocked out is known as the stop band.[1] Finite Impulse Response, filters are one of the primary types of filters used in Digital Signal Processing. For the design of Low pass FIR filters complex calculations are required. Mathematically, by substituting the values of Pass band, transition width, pass band ripple, stop band attenuation, sampling frequency in any of the methods from window method, frequency sampling method or optimal method we can get the values of filter coefficients h(n)[2] For removing noise or cancellation of noise we use various type of digital filter. In this paper we propose design technique of bandpass FIR filter using various type of window function. Kaiser window is the best window function in FIR filter design. Using this window we can realize that FIR filter is simple and fast.