A Novel Kernel Algorithm for Finite Impulse Response Channel Identification

Semi-blind identification of finite impulse response channels

It is a standard result that a finite impulse response channel of length L can be uniquely identified by feeding in a known (and persistently exciting) sequence of 2L 1 consecutive data points. Equivalently, given only 2L 2 consecutive data points, the channel can be uniquely identified up to a multiplicative constant. This paper significantly extends the identifiability criterion to the case w...

Novel Approach of Designing Multiplier-less Finite Impulse Response Filter using Differential Evolution Algorithm

Reduction of computational complexity of digital hardware has drawn the special attention of researchers in recent past. Proper emphasis is needed in this regard towards the settlement of computationally efficient as well as functionally competent design of digital systems. In this communication, we have made one novel attempt for designing multiplier-free Finite duration Impulse Response (FIR)...

Interpolated Finite Impulse Response (IFIR)

The finite impulse response filters are inherently stable and have linear phase response property. The main drawback of these filters is lies in requirement of higher orders for similar magnitude response compared to Infinite Impulse response filters. Also the amount of computational complexity needed for the implementation of the filter, especially for the filters with narrow transition band i...

Finite Impulse Response Neural Networks

A neural network architecture, which models synapses as Finite Impulse Response (FIR) linear lters, is discussed for use in time series prediction. Analysis and methodology are detailed in the context of the Santa Fe Institute Time Series Prediction Competition. Results of the competition show that the FIR network performed remarkably well on a chaotic laser intensity time series.

Finite Impulse Response ( FIR ) Filters