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Topic: Adaptive filter

	Adaptive filter - Wikipedia, the free encyclopedia
		Generally speaking, the adapting process involves the use of a cost function, which is a criterion for optimum performance of the filter (for example, minimizing the noise component of the input), to feed an algorithm, which determines how to modify of the filter coefficients to minimize the cost on the next iteration.
		The variable filter estimates the desired signal by convolving the input signal with the impulse response.
		The adaptive filter would take input both from the patient and from the power supply directly and would thus be able to track the actual frequency of the noise as it fluctuates.
	en.wikipedia.org /wiki/Adaptive_filter (612 words)

	Adaptive Signal Processing JAVA Applet
		Adaptive DSP is one of the most important areas of signal processsing, and provides the core algorithmic means to implement applications ranging from mobile telephone speech coding, to noise cancellation, to communication channel equalization.
		Adaptive active noise cancellation is another hi-tech and mature technology found in the cabins of some airliners to reduce the level of noise.
		Note the common element in these structures is the general adaptive signal processor, as depicted in Figure 2, with the input signal x(k), the output signal y(k), the desired signal d(k) and the error signal e(k).
	www.ewh.ieee.org /soc/es/May2001/19/Begin.htm (1397 words)

	[No title] (Site not responding. Last check: 2007-10-13)
		The plurality of filter stages have a common equalisation control signal that has a magnitude that corresponds to the communications path transfer function, with each adaptive filter stage transfer function being an approximate inverse of a transfer function that corresponds to a portion of the input data signal communications path.
		With non-linear signal filtering behaviour it is meant that the quality of the filtering behaviour depends on the signal input, and that the filtering behaviour is not a mere linear combination of inverse functions of the ideal transfer functions of the transmission channel.
		In the adaptive equalizer according to the present invention, the linear filtering behaviour of the adaptive amplification compensation stages, receiving tuning parameters all having a binary value, may be compensating substantially ideally for the signal losses in a part of the transmission line.
	www.wipo.int /cgi-pct/guest/getbykey5?KEY=04/73274.040826&ELEMENT_SET=DECL (8807 words)

	Adaptive filter: Encyclopedia topic (Site not responding. Last check: 2007-10-13)
		An adaptive filter is a digital filter (digital filter: in electronics, a digital filter is any electronic filter that works by performing...
		By way of contrast, a non-adaptive filter has static filter coefficients (which collectively form the transfer function (transfer function: a transfer function is a mathematical representation of the relation between the input and...
		Kalman filter (Kalman filter: the kalman filter is an efficient recursive filter which estimates the state of a dynamic...
	www.absoluteastronomy.com /reference/adaptive_filter (446 words)

	[No title]
		The filter must be adjusted to pass, without corruption, the desired components of the input signal and to remove the undesired components.
		The adaptive filter must have a long-impulse response to produce a FIR filter with a sharp cutoff frequency.
		In the case of adaptive filtering, this parameter is the error signal between the desired signal and the output of the adaptive filter.
	www.evaluationengineering.com /archive/articles/0697ess.htm (1553 words)

	Adaptive FIR Filtering
		The known input signal is fed through the adaptive filter in an effort to duplicate the unknown system output.
		Adaptive filters are used in modern telephony to perform echo suppression.
		Use the filter coefficients to plot, in MATLAB, the magnitude and phase responses of the estimated filter.
	cnx.org /content/m11801/latest (684 words)

	Designing Adaptive Filters (Filter Design Toolbox)
		Cascading the adaptive filter with the unknown filter causes the adaptive filter to converge to a solution that is the inverse of the unknown system.
		In the cascaded filters case, like this one, the unknown filter results in a delay in the signal arriving at the summation point after both filters.
		As a reminder, the unknown filter was a lowpass filter with cutoff at 0.55, on the normalized frequency scale from 0 to 1.
	www.weizmann.ac.il /matlab/toolbox/filterdesign/adapti15.html (1008 words)

	Royal Consortium for DSP - Design Approach and Procedure
		One category, of which the Kalman filter is a representative example, requires that there be knowledge of the state space of the system to which the filter is being applied.
		The difference between the FIR and LMS filter is that after each sample is processed, the output signal is compared to some reference signal and via some algorithm, the weights are updated in and LMS adaptive filter.
		In essence, the filter is always one sample behind the input, and if its reference signal is to go to zero, it must "guess" what the next sample will be so that it can generate the correct output so that the reference signal goes to zero.
	www.herberts.org /wayne/proj431/projdes.htm (2075 words)

	Designing Adaptive Filters (Filter Design Toolbox) (Site not responding. Last check: 2007-10-13)
		In this case, the unknown filter is one of the filters used in the examples from gremez Examples -- the constrained lowpass filter.
		From the figure you see that the filter is indeed lowpass and constrained to 0.2 ripple in the stopband.
		With this as the baseline, the adaptive LMS filter examples use the adaptive LMS algorithms and their initialization functions, to identify this filter in a system identification role.
	www.weizmann.ac.il /matlab/toolbox/filterdesign/adaptiv9.html (379 words)

	Adaptive Filter Design with Ride - Tutorial - Development Library - National Instruments
		An adaptive filter is a filter containing coefficients that are updated by some type of adaptive algorithm to improve or somehow optimize the filter’s response to a desired performance criterion.
		In general, adaptive filters consist of two basic parts: the filter which applies the required processing on the incoming signal which is to be filtered; and an adaptive algorithm, which adjusts the coefficients of that filter to somehow improve its performance.
		The adaptive algorithm will continuously adjust the coefficients, or tap weights, in the filter to minimize the error, e(n), between the filtered output, y(n), and a signal representing the desired response of the filter, d(n).
	zone.ni.com /devzone/conceptd.nsf/webmain/064159BD9C2C42FD86256FFE00171ACB (1234 words)

	Elec 301 Project (Site not responding. Last check: 2007-10-13)
		The LMS algotrithm updates the filter coefficients to minimize the error between the primary signal and the filtered noise.
		The one important condition on the use of adative filters for noise cancellation is that the noise can't be similar to the desired voice signal.
		The figure below shows the output of the adaptive filter when the reference noise used was a sinusoid of the same frequency as that of the voice signal plus some white noise.
	www.owlnet.rice.edu /~elec301/Projects00/site/design.html (968 words)

	Adaptive Identification and Inverse Filtering using Java
		This impulse is filtered by the path characteristics, producing the output shown by the red trace, and is also filtered by the adaptive filter, producing the output shown by the blue trace.
		For an inverse filter, the path output data is fed to the adaptive engine as the input to the adaptive filter, and the wideband data is fed to the adaptive engine as the target.
		The impulse response of the adaptive filter is shown in the left panel of Figure 9, progressing from the beginning to the end of the run.
	www.developer.com /java/other/article.php/3583241 (6416 words)

	LMS Adaptive Filter (DSP Blockset)
		Compute filter estimates for an input using the LMS adaptive filter algorithm.
		The LMS Adaptive Filter block implements an adaptive FIR filter using the stochastic gradient algorithm known as the normalized Least Mean-Square (LMS) algorithm.
		The FIR filter length parameter specifies the length of the filter that the LMS algorithm estimates.
	www.cs.berkeley.edu /titan/sww/software/matlab/toolbox/dspblks/lmsadaptivefilter.html (282 words)

	Adaptive Noise Cancellation
		The basic idea of an adaptive noise cancellation algorithm is to pass the corrupted signal through a filter that tends to suppress the noise while leaving the signal unchanged.
		From the recorded primary input and the filtered output, we can see the ratio of the speech signal to the background noise is obviously increased in the output compared to that in the primary input.
		The results show that LMS is an effective algorithm used for the adaptive filter in the noise canceling implementation.
	www-ece.rice.edu /~klwang/elec434/elec434.htm (1330 words)

	Kalman Adaptive Filter (DSP Blockset) (Site not responding. Last check: 2007-10-13)
		The Kalman Adaptive Filter block computes the optimal linear minimum mean-square estimate (MMSE) of the FIR filter coefficients using a one-step predictor algorithm.
		The Kalman filter assumes that there are no deterministic changes to the filter taps over time (i.e., the transition matrix is identity), and that the only observable output from the system is the filter output with additive noise.
		The FIR filter length parameter specifies the length of the filter that the Kalman algorithm estimates.
	www.ece.umr.edu /computing/unix/software/matlab/toolbox/dspblks/kalmanadaptivefilter.html (454 words)

	RLS Adaptive Filter (DSP Blockset)
		Compute filter estimates for an input using the RLS adaptive filter algorithm.
		The RLS Adaptive Filter block recursively computes the least-squares estimate (RLS) of the FIR filter coefficients based on an externally generated error signal.
		The FIR filter length parameter specifies the length of the filter that the RLS algorithm estimates.
	www.tau.ac.il /cc/pages/docs/matlab/help/toolbox/dspblks/rlsadaptivefilter.html (236 words)

	DScaler -- Adaptive Noise Filter
		The Adaptive Noise filter examines the image, infers the amount of noise in the picture, and uses that estimate to determine how to cancel the noise.
		Gradual Noise filter, the degree of certainty about motion and noise is used to decide what mix of the previous and current colors to show.
		The Adaptive Noise filter is more tolerant of interference right after it starts up, before it has seen a clean signal from another source.
	deinterlace.sourceforge.net /Help/AdaptiveNoise.htm (1650 words)

	Designing Adaptive Filters (Filter Design Toolbox)
		Both the adaptive LMS function to use and the matching initialization function to set up the adapting algorithm.
		With the unknown filter designed and the desired signal in place you can apply the adaptive LMS filter to identify the unknown.
		In the stem plot the actual and estimated filter weights are the same.
	www.weizmann.ac.il /matlab/toolbox/filterdesign/adapti10.html (504 words)

	Designing Adaptive Filters (Filter Design Toolbox) (Site not responding. Last check: 2007-10-13)
		As the signal into the filter continues, the adaptive filter coefficients adjust themselves to achieve the desired result, such as identifying an unknown filter or cancelling noise in the input signal.
		An adaptive FIR or IIR filter designs itself based on the characteristics of the input signal to the filter and a signal which represent the desired behavior of the filter on its input.
		The adaptive filter functions in this toolbox implement the shaded portion of Figure 3-1, replacing the adaptive algorithm with an appropriate technique.
	www.weizmann.ac.il /matlab/toolbox/filterdesign/adaptiv2.html (335 words)

	Adaptive Filtering: LMS Algorithm (Site not responding. Last check: 2007-10-13)
		The adaptive filter adjusts its coefficients to minimize the mean-square error between its output and that of an unknown system.
		The adaptive filter, W, is adapted using the least mean-square algorithm, which is the most widely used adaptive filtering algorithm.
		Because the goal is to minimize the error, however, equation 1 updates the filter coefficients in the direction opposite the gradient; that is why the gradient term is negated.
	cnx.org /content/m10481/latest (944 words)

	Adaptive LMS Filter (Site not responding. Last check: 2007-10-13)
		The on chip adaptive filter operates in the frequency domain and outputs a clean signal.
		The filter bank was divided in two main blocks - the first eight filters cover the low frequencies while the other eight cover the high frequencies.
		The high frequency filters use the same gm-stages but have smaller capacitors (80fF and 320fF). Each filter is biased using a current that is then mirrored into the corresponding gm stages.
	bach.ece.jhu.edu /gert/classes/492/2005/LMS (588 words)

	Acoustic Echo Canceller using Block Frequency Domain Adaptive Filter
		The adaptive filter is set to have 512 coefficients with 128 samples processed per block.
		This is the time needed for the filter to adjust itself to reach a reasonable approximation of the room impulse response between Spkr and Mic, and consequently, resulting in a reasonable echo reduction.
		The adaptive filter is allowed to adapt only when the remote speaker is active and the local speaker is not active.
	www.dspalgorithms.com /bfdafaec/bfdafaec11.html (2728 words)

	Designing Adaptive Filters (Filter Design Toolbox)
		Without going into details because the specifics are beyond the scope of this User's Guide, the adaptive filter functions in the toolbox represent variations of Kalman filtering.
		Thus, Kalman filters are the basis of all the other functions, and perhaps the most effective and efficient since each succeeding filter update in the Kalman algorithm depends only on the most recent input data.
		Total number of iterations in the adaptive filter run.
	www.technion.ac.il /guides/matlab/toolbox/filterdesign/adapti16.html (273 words)

	Mapping LMS Adaptive Filter IP Core to Multiplier-Array FPGA Architecture for High Channel-Density VOIP Line Echo ...
		The LMS adaptive filter is the main functional block in high channel-density line echo cancellers for VOIP.
		The main computation-intensive block among them is the adaptive filter engine which generates the replica of the reflected echo.
		In LMS adaptive FIR filter, the filter coefficients are updated using the LMS algorithm to be described briefly in the next section.
	www.us.design-reuse.com /articles/article5868.html (1948 words)

	KVR : Sonalksis releases TBK Adaptive Resonance Filter
		Standard filters require the alteration of resonance with frequency to maintain stable sonic attributes, particularly when resonance or saturation levels are elevated.
		However the TBK 'adaptive resonance' system uses a psychoacoustic model to ensure a faultless sound regardless of filter style, frequency settings or sweep motions.
		'Adaptive Resonance' is the technology in the Sonalksis TBK that controls the interaction between frequency, resonance and circuit saturation with respect to this psychoacoustic model, in order to give an improved sonic aesthetic in any circumstances.
	www.kvraudio.com /news/4456.html (299 words)

	A Subband Adaptive Filter - Harteneck, Stewart (ResearchIndex)
		The filter bank consists of at least three channels which are subsampled by different subsampling ratios.
		In this paper we investigate into the applicability of this filter bank for adaptive subband filtering and compare the setup with existing subband and fullband techniques.
		INTRODUCTION One of the main problems in adaptive filtering is the computational complexity of the adaptive...
	citeseer.ist.psu.edu /168117.html (524 words)

	Annoyance Filter: Adaptive Junk Mail Filter
		The Annoyance Filter is a program which exploits the indelible signature of advertising to identify it before it ever reaches the eyes of the reader, with a very low likelihood of junk mail being confused with legitimate messages.
		From these archives, Annoyance Filter computes statistics for the words which appear in the two collections of messages, determining for each the probability that its appearing in a message is indicative of junk mail.
		Given that Annoyance Filter is standard C++ (and the ubiquity of gcc in any case), porting the program isn't the big problem--it's the integration of filtering with the mail processing system, plus whatever is needed to transform the mail system's archives into the Unix mail folder format the program uses while training.
	www.fourmilab.ch /annoyance-filter (2577 words)

	Haar Wavelet Filter and Adaptive Median Filter (Site not responding. Last check: 2007-10-13)
		This filter is macro-recordable, and an example macro is provided that helps finding suitable coefficients for a given image type.
		The wavelet filter is good at removing gaussian-type noise, while it can leave some kind of photon noise (very hot pixels for example).
		This filter will detect pixels that differ from their context by more than a given multiple of the neighborhood's standard deviation.
	rsb.info.nih.gov /ij/plugins/haar-wavelet-filter.html (329 words)

	Evolving an Adaptive Digital Filter - Tufte, Haddow (ResearchIndex)
		In a non-adaptive filter, characteristics of the filter may be refined to remove noise.
		One method of achieving this is to use evolution to decide the filter characteristics.
		However, if the noise level is sufficient or the input signal is not of the required type for the output signal required, then a satisfactory output signal may not be achievable.
	citeseer.ist.psu.edu /424559.html (375 words)

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