Digital filter

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An FIR filter

In electronics, a digital filter is any electronic filter that works by performing digital mathematical operations on an intermediate form of a signal. This is in contrast to older analog filters which work entirely in the analog realm and must rely on physical networks of electronic components (such as resistors, capacitors, transistors, etc.) to achieve the desired filtering effect.

Digital filters can achieve virtually any filtering effect that can be expressed as a mathematical function or algorithm. The two primary limitations of digital filters are their speed (the filter can't operate any faster than the computer at the heart of the filter), and their cost. However as the cost of integrated circuits has continued to drop over time, digital filters have become increasingly commonplace and are now an essential element of many everyday objects such as radios, cellphones, and stereo receivers.

1 Digital filter advantages
2 Types of digital filters
3 References
4 See also
5 External links

[edit] Digital filter advantages

Digital filters can easily realize performance characteristics far beyond what are implementable with analog filters. It is not particularly difficult, for example, to create a 1000 Hz low-pass filter which can achieve near-perfect transmission of a 999 Hz input while entirely blocking a 1001 Hz signal. Analog filters cannot discriminate between such closely spaced signals.

Also, for complex multi-stage filtering operations, digital filters have the potential to attain much better signal to noise ratios than analog filters. This is because whereas at each intermediate stage the analog filter adds more noise to the signal, the digital filter performs noiseless mathematical operations at each intermediate step in the transform. The primary source of noise in a digital filter is to be found in the initial ADC - analog to digital conversion step, where in addition to any circuit noise introduced, the signal is subject to an unavoidable quantization error which is due to the finite resolution of the digital representation of the signal.

Note also that frequency components exceeding half the sampling rate of the filter (cf. Nyquist sampling theorem) will be confounded (or aliased) by the filter. Thus a small anti-aliasing filter is always placed ahead of the analog to digital conversion circuitry to prevent these high-frequency components from aliasing.

[edit] Types of digital filters

Many digital filters are based on the Fast Fourier transform, a mathematical algorithm that quickly extracts the frequency spectrum of a signal, allowing the spectrum to be manipulated (such as to create pass-band filters) before converting the modified spectrum back into a time-series signal.

Another form of a typical linear digital filter, expressed as a transform in the Z-domain, is

$H(z) = \frac{B(z)}{A(z)} = \frac{{b_{0}+b_{1}z^{-1}+b_{2}z^{-2} + \cdots + b_{N}z^{-N}}}{{1+a_{1}z^{-1}+a_{2}z^{-2} + \cdots +a_{M}z^{-M}}}$

where M is the order of the filter. See Z-transform's LCCD equation for further discussion of this transfer function.

This form is for an infinite impulse response filter, but if the denominator is unity then this is the form for a finite impulse response filter.

Another form of a digital filter is that of a state space model. A well used state-space filter is the Kalman filter published by Rudolf Kalman in 1960.

[edit] References

A. Antoniou, Digital Filters: Analysis, Design, and Applications, New York, NY: McGraw-Hill, 1993.
S.K. Mitra, Digital Signal Processing: A Computer-Based Approach, New York, NY: McGraw-Hill, 1998.
A.V. Oppenheim and R.W. Schafer, Discrete-Time Signal Processing, Upper Saddle River, NJ: Prentice-Hall, 1999.
J.F. Kaiser, Nonrecursive Digital Filter Design Using the Io-sinh Window Function, Proc. 1974 IEEE Int. Symp. Circuit Theory, pp. 20-23, 1974.
S.W.A. Bergen and A. Antoniou, Design of Nonrecursive Digital Filters Using the Ultraspherical Window Function, EURASIP Journal on Applied Signal Processing, vol. 2005, no. 12, pp. 1910-1922, 2005.
T.W. Parks and J.H. McClellan, Chebyshev Approximation for Nonrecursive Digital Filters with Linear Phase, IEEE Trans. Circuit Theory, vol. CT-19, pp. 189-194, Mar. 1972.
L. R. Rabiner, J.H. McClellan, and T.W. Parks, FIR Digital Filter Design Techniques Using Weighted Chebyshev Approximation, Proc. IEEE, vol. 63, pp. 595-610, Apr. 1975.
A.G. Deczky, Synthesis of Recursive Digital Filters Using the Minimum p-Error Criterion, IEEE Trans. Audio Electroacoust., vol. AU-20, pp. 257-263, Oct. 1972.

[edit] See also

[edit] External links

WinFilter – Free filter design software
Filtplot – Free customizable digital filter design software built with python and boost (WinXP/Ubuntu 6.10/RHEL-4). Also with interactive web interface.
DISPRO – Free filter design software
Java demonstration of digital filters
IIR Explorer educational software
FIWIZ – Filter design wizard (FIR, IIR)

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Categories: Filter theory | Digital signal processing | Synthesiser modules