Patra , Manas Ranjan (2013) *study of adaptive signal processing.* BTech thesis.

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## Abstract

An adaptive filter is a digital filter that can adjust its coefficients to give the best match t An

adaptive filter is a digital filter that can adjust its coefficients to give the best match to a given

desired signal. When an adaptive filter operates in a changeable environment the filter

coefficients can adapt in response to changes in the applied input signals. Adaptive filters

depend on recursive algorithms to update their coefficients and train them to near the optimum

solution. An everyday example of adaptive filters is in the telephone system where, impedance

mismatches causing echoes of a signal are a significant source of annoyance to the users of the

system. The adaptive signal process is here to estimate and generate the echo path and

compensate for it. To do this the echo path is viewed as an unknown system with some impulse

response and the adaptive filter must mimic this response.

Adaptive Filters are generally implemented in the time domain which works well in most

scenarios however in many applications the impulse response become long, and increasing the

complexity of the filter beyond a level where it can no longer be implemented efficiently in the

time domain. An example of acoustic echo cancellation applications is in hands free telephony

system. However there exists an alternative solution and that is to implement the filters in the

frequency domain. The Discrete Fourier Transform or Fast Fourier Transform (FFT) allows the

conversion of signals from the time domain to the frequency domain in an efficient manner.

Despite the efficiency of the FFT the overhead involved in converting the signals to the

frequency domain does place a restriction on the use of the algorithm. When the impulse

response of the unknown system and hence the impulse response of the filter is long enough

however this is not an issue since the computational cost of the conversion is much less than that

of the time domain algorithm. The actual filtering of the signals requires little computational

cost in the frequency domain. Investigation of the so-called crossover point, the point where the

frequency domain implementation becomes more efficient than the time domain implementation

is important to establish the point where frequency domain implementation becomes practical

Item Type: | Thesis (BTech) |
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Uncontrolled Keywords: | FIR filter; IIR filter; Adaptive filter; frequency domain adaptive filter |

Subjects: | Engineering and Technology > Electronics and Communication Engineering > Adaptive Systems |

Divisions: | Engineering and Technology > Department of Electronics and Communication Engineering |

ID Code: | 5183 |

Deposited By: | Hemanta Biswal |

Deposited On: | 10 Dec 2013 16:22 |

Last Modified: | 20 Dec 2013 10:45 |

Supervisor(s): | Sahoo, U K |

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