Showing papers on "Kernel adaptive filter published in 1994"

Adaptive digital notch filter design on the unit circle for the removal of powerline noise from biomedical signals

Abstract: Investigates adaptive digital notch filters for the elimination of powerline noise from biomedical signals. Since the distribution of the frequency variation of the powerline noise may or may not be centered at 60 Hz. Three different adaptive digital notch filters are considered. For the first case, an adaptive FIR second-order digital notch filter is designed to track the center frequency variation. For the second case, the zeroes of an adaptive IIR second-order digital notch filter are fixed on the unit circle and the poles are adapted to find an optimum bandwidth to eliminate the noise to a pre-defined attenuation level. In the third case, both the poles and zeroes of the adaptive IIR second-order filter are adapted to track the center frequency variation within an optimum bandwidth. The adaptive process is considerably simplified by designing the notch filters by pole-zero placement on the unit circle using some suggested rules. A constrained least mean-squared algorithm is used for the adaptive process. To evaluate their performance, the three adaptive notch filters are applied to a powerline noise sample and to a noisy EEG as an illustration of a biomedical signal. >

An efficient recursive total least squares algorithm for FIR adaptive filtering

Abstract: An algorithm for recursively computing the total least squares (TLS) solution to the adaptive filtering problem is described. This algorithm requires O(N) multiplications per iteration to effectively track the N-dimensional eigenvector associated with the minimum eigenvalue of an augmented sample covariance matrix. It is shown that the recursive least squares (RLS) algorithm generates biased adaptive filter coefficients when the filter input vector contains additive noise. The TLS solution on the other hand, is seen to produce unbiased solutions. Examples of standard adaptive filtering applications that result in noise being added to the adaptive filter input vector are cited. Computer simulations comparing the relative performance of RLS and recursive TLS are described. >

Least mean p-power error criterion for adaptive FIR filter

Abstract: An adaptive FIR filter based on the least mean p-power error (MPE) criterion is investigated. First, some useful properties of MPE function are studied. Three main results are as follows: 1) MPE function is a convex function of filter coefficients; so it has no local minima. 2) When input process and desired process are both Gaussian processes, then MPE function has the same optimum solution as the conventional Wiener solution for any p. 3) When input process and desired process are non-Gaussian processes, then MPE function may have better optimum solution than Wiener solution. Next, a least mean p-power (LMP) error adaptive algorithm is derived and some application examples are presented. Consequently, when the signal is corrupted by an impulsive noise, the adaptive algorithm with p=1 is preferred. Furthermore, when the signal is corrupted by noise or interference, the adaptive algorithm with proper choice of p may be preferred. >

Encoding and decoding video signals using adaptive filter switching criteria

Abstract: Reference frames are generated by selectively filtering blocks of decoded video frames. The decision whether to filter a block is based on a comparison of an energy measure value generated for the block and an energy measure threshold value corresponding to the quantization level used to encode the block. The energy measure threshold value for a given quantization level is selected by analyzing the results of encoding and decoding training video frames using that quantization level. The reference frames are used in encoding and decoding video frames using interframe processing.

Orthogonal time-varying filter banks and wavelet packets

Abstract: Considers the construction of orthogonal time-varying filter banks. By examining the time domain description of the two-channel orthogonal filter bank the authors find it possible to construct a set of orthogonal boundary filters, which allows to apply the filter bank to one-sided or finite-length signals, without redundancy or distortion. The method is constructive and complete. There is a whole space of orthogonal boundary solutions, and there is considerable freedom for optimization. This may be used to generate subband tree structures where the tree varies over time, and to change between different filter sets. The authors also show that the iteration of discrete-time time-varying filter banks gives continuous-time bases, just as in the stationary case. This gives rise to wavelet, or wavelet packet, bases for half-line and interval regions. >

Optimum loop filter in hybrid coders

Abstract: Examines the role of the loop/interpolation filter in the motion compensation loop of hybrid coders. Using the Wiener filtering concept and the statistical model developed by Chen and Pang (1992), the optimum filter that minimises the prediction error has been found. The result is expressed in an explicit form in terms of a correlation parameter, /spl rho/ and an inaccuracy parameter, /spl alpha/. It explains many current practices in MPEG and H.261 coders, as well as the leakage predictor, 3-tap versus 8-tap filters and other related issues. The analysis shows that minimum bit rate can only be achieved if the loop filter matches the statistical characteristic of the motion-compensated signal. Furthermore, since the motion noise characteristic could be very different in the horizontal and vertical direction for many sequences, the decision to deploy the optimum filter should be made separately in the two directions. The paper also derives the scalar loop filter in DCT domain. The scalar filter is sub-optimal, but it requires less computational load than the spatial domain filter (64 versus 484 multiplications per 8/spl times/8 block). Experiments show that it performs almost as efficiently as the optimum 3-tap spatial domain filter, thus ascertaining that its performance has not been significantly compromised by the scalar requirement. Experimental simulations on test sequences confirm the theoretical optimum results, and indirectly show that the simple statistical model used in the derivation is adequate. >

Optical wavelet matched filter.

Abstract: A shift-invariant optical continuous wavelet transform is used for pattern recognition. We propose an optical wavelet matched filter that performs optical wavelet transforms for edge enhancement and the correlation between two wavelet transforms in a single step. This new bandpass matched filter shows improved discrimination capability with respect to the conventional matched filter and improved signal-to-noise ratio with respect to the phase-only matched filter. The wavelet matched filter provides flexibility of an adaptive choice of the scale factors of the wavelets that permit the selection of size and orientation of the smoothing function used in edge enhancement and the optimization of the performance of the filter. Optical experimental results are shown.

Adaptive Compensation of Piezoelectric Sensoriactuators

Abstract: An adaptive filter is used to estimate the feedthrough capacitance of a piezoelectric sensoriactuator in this work. The mechanical response of the piezostructure is resolved from the electrical response of the piezoelectric device through standard adaptive signal processing tech niques. Two common adaptive algorithms are reviewed for the given application: the LMS and the RLS. For spectrally white inputs the adaptation of the digital compensator yields a filter output which is proportional to the electrical response of the piezoelectric device. Thus, the remaining elec trical signal consists of the charge due to the mechanical response of the piezostructure. The adap tive filter converges to a combination of the feedthrough capacitance and the real portion of the mechanical piezostructure response, and the filter error is the quadrature component of the mechanical response. Preliminary results from the theoretical analysis and numerical simulations indicate that, under certain conditions, adaptive signal ...

Detection and estimation using an adaptive rational function filter

Abstract: Proposes a new nonlinear adaptive filter structure based on rational functions. There are several advantages to the use of this filter. First, it is a universal approximator and a good extrapolator. Second, it ran be trained by a linear adaptive algorithm, which makes it suitable for real-time adaptive signal processing. Third, it has a best approximation for a specified function. To demonstrate its utility as a tool for solving adaptive signal processing problems, the authors apply the adaptive rational function filter to the problem of estimation and detection. The estimation problem pertains to the direction of arrival (DOA) estimation problem in array signal processing. For the detection problem, the authors consider the detection of a weak radar target (a small piece of ice) in an ocean environment. >

Filter evaluation and selection in wavelet image compression

Abstract: Choice of filter bank in wavelet compression is a critical issue that affects image quality as well as system design. Although regularity is sometimes used in filter evaluation, its success at predicting compression performance is only partial. A more reliable evaluation can be obtained by considering an L-level synthesis/analysis system as a single-input, single-output, linear shift-variant system with a response that varies according to the input location modulo (2/sup L/, 2/sup L/). By characterizing a filter bank according to its impulse response and step response in addition to regularity, the authors obtain reliable and relevant (for image coding) filter evaluation metrics. Using this approach, they have evaluated all possible reasonably short (less than 34 taps in the synthesis/analysis pair) minimum order biorthogonal wavelet filter banks. Of this group of over 4300 candidate filter banks, they have selected and presented the filters best suited to image compression. While some of these filters have been published previously, others are new and have properties that make them attractive in system design. >

Complex adaptive IIR notch filter algorithm and its applications

Abstract: In this paper, conventional real coefficient adaptive notch filters (ANF's) are extended to complex coefficient ones. This complex adaptive notch filter is implemented as a constrained IIR filter using a complex Gauss-Newton type algorithm to adjust its coefficients. When the ANF algorithm is applied to estimate the frequencies of sinusoids embedded in white noise. The results show that this algorithm has fast convergence, small bias, and achieves the Cramer-Rao bound. Furthermore, this ANF algorithm is used to estimate the parameters of multiple chirp signals. Simulation results also demonstrate very good performance. Finally, when this ANF algorithm is used to suppress narrowband interference in QPSK spread spectrum communication systems, the analytic result reveals that its signal-to-noise ratio improvement factor is grater than the factor of conventional one-sided prediction filter. >

Demodulation system having adaptive matched filter and decision feedback equalizer

Abstract: In a modulation system, a demodulator demodulates an intermediate frequency modulated signal and outputs an analog-baseband signal, and an analog-digital converter analog-digital converts this baseband signal. An adaptive matched filter inputs the output of the analog-digital converter and makes symmetrical the impulse response of the propagation path. A decision feedback equalizer inputs the output of the adaptive matched filter and eliminates the intersymbol interference. A reset circuit judges the fading type using tap coefficients within the decision feedback equalizer, and stops the operation of the adaptive matched filter in cases of minimum phase shift type fading. The adaptive matched filter is constructed so as to operate in an intermediate frequency band as well as in a baseband.

Method of and system for enhancing distorted graphical information

Abstract: A system for and method of enhancing image/video signals to be decoded is disclosed The system for and method of post-filtering uses, preferably, a temporal filter (eg, 110) and a spatial filter (eg, 112), both of which are adaptive but neither is required to be adaptive However, the system for and method of post-filtering may also be used with only an adaptive spatial post-filter In this case, the performance is upper-bounded by the performance of systems using both the adaptive temporal and adaptive spatial post-filter

Time-varying adaptive filters for evoked potential estimation

Abstract: Adaptive implementation of an optimal time-varying filter (TVF) for evoked potential (EP) estimation is addressed here A data-adaptive scheme is used, which converges asymptotically to the optimal TVF solution Two basic adaptive TVF's (ATVF's) are first introduced, namely least mean square (LMS) ATVF and recursive least-squares (RLS) ATVF The latter converges much faster than the former Since the basic ATVF's usually require a relatively large set of response trials to get a meaningful solution, a reduced-order ATVF is further presented and the corresponding LMS and RLS (including a fast RLS) adaptive algorithms are developed To save memory, a truncated Fourier expansion is suggested to express approximately the time-sequenced weight-vectors of the ATVF's, resulting in a simplified reduced-order ATVF Finally, extensive simulations are provided to confirm the superior performance of the ATVF's The present ATVF's can be used as prefilters for latency-corrected average (LCA) processing to obtain more informative estimates of EP signals >

Advanced in-plane rotation-invariant correlation filters

Abstract: Advanced correlation filter synthesis algorithms to achieve rotation invariance are described. We use a specified form for the filter as the rotation invariance constraint and derive a general closed-form solution for a multiclass rotation-invariant filter that can recognize a number of different objects. By requiring the filter to minimize the average correlation plane energy, we produce a multiclass rotation invariant (RI) RI-MACE filter, which controls correlation plane sidelobes and improves discrimination against false targets. To improve noise performance, we require the filter to minimize a weighted sum of correlation plane signal and noise energy. Initial test results of all filters are provided. >

A new interpretation of the fault detection filter Part 1: Closed-form algorithm

Abstract: A novel interpretation is presented of the detection filter in the context of an eigenstructure assignment problem. The detection filter is shown to be equivalent to the combination of two decoupled observers, with the advantage that theories already developed for conventional observers can be utilized as design aids. Detection space and detection order are re-defined accordingly, and it is shown that of the two observers that constitute a detection filter, the one associated with the detection space is a single-output system. This fact is important since it explains important properties of the fault detection filter in a very uncomplicated fashion, leading to a clear interpretation of the freedom available in designing the filter; in particular, it is proven that the detection filter gains are unique, given the eigenvalues of the detection space. Further, the formulation leads to a closed-form expression for the detection filter, and is therefore well-suited to the development of simple design algorithms.

Blind adaptive interference suppression for near-par resistant CDMA

Abstract: Multiuser detection techniques can potentially solve the near-far problem in code-division multiple-access (CDMA) systems. However, these techniques often assume knowledge of system parameters, suck as signature waveforms for all users, and associated timing, which may not be available, or may be inconvenient to obtain in practice. Recently proposed adaptive minimum mean squared error (MMSE) detectors do not require knowledge of signature waveforms; however, these techniques require a training sequence for adaptation. Here we propose a blind multiuser linear detector which requires only knowledge of the desired user's signature sequence (and associated timing). In particular, it does not require the use of a training sequence. Our approach is to decompose the filter impulse response into the sum of two orthogonal components: the matched filter corresponding to the desired user plus an adaptive filter. We show that if the adaptive filter is chosen to minimize the energy (i.e., variance) of output samples at each symbol interval, then a scaled version of the MMSE detector is obtained. Based on this observation, a simple adaptive gradient algorithm is derived, and numerical examples are presented which illustrate its performance in a synchronous CDMA system.

Adaptive filter for correcting the transfer characteristic of electroacoustic transducer

Abstract: An arrangement is provided for converting an electric signal into an acoustic or a mechanic signal comprising a transducer (11), a linear or nonlinear filter (1) with controllable parameters, a sensor (12), a controller (24), a reference filter (20) and a summer (17). The filter (1) is connected to the electric input of the transducer and is adaptively adjusted to compensate for the linear and/or nonlinear distortions of the transducer and to realize a desired overall transfer characteristic. The filter has for every controllable filter parameter an additional output (7) supplying a gradient signal to the controller and a control input (10). The summer (17) provides an error signal derived from the sensor output and reference filter output. The controller contains a circuit (53) for filtering the gradient signal and/or a circuit (25) for filtering the error signal, a multiplier (51) and an integrator (57) for producing a control signal to update every filter parameter. This arrangement omits off-line pre-training and adapts on-line for changing transducer characteristics caused by temperature, ageing and so on.

Adaptive equalizer for magnetic reproducing apparatus

Abstract: The characteristic of a regenerative signal from a magnetic head 11 is compensated by a filter 14 serving as an equalizer. The regenerative signal thus compensated is then decoded at a decoder 15. An adaptive control unit 17 adjusts (modifies) the characteristic of the filter 14 on the basis of a decode error (residual) at the decoder 15 and an input to the filter 14. A servo control unit 18 sends a servo lock signal to the adaptive control unit 17 when a servo control operation at the time of reproduction is stabilized to start an automatic adjustment operation of the filter characteristic. Thus, it is possible to prevent in advance bad influence or effect on a compensating operation of the equalizer resulting from the fact that an adaptive adjustment operation of the filter characteristic might be carried out at the time when the servo control operation is unstable like at the time of building up of a reproducing operation.

Wave‐equation extrapolation‐based multiple attenuation: 2-D filtering in the f-k domain

Abstract: A new nonlinear filter for wave-equation extrapolation-based multiple suppression is designed in the f-k domain. The realization of the new filter in the f-k domain is an extension of the conventional f-k dip filter. However, the new demultiple filter is superior to the conventional f-k dip filter in the sense that the multiple reject zones are determined automatically (based on the information of the input original data and the multiple model traces obtained by the waveextrapolation method) rather than by prior information on multiple moveout (dip) range. Therefore, it can easily cope with situations such as aliasing and the mixture of energy from multiples and primaries in the same quadrant. The new filter is smooth on the boundary of the reject area. Numerical examples demonstrate that the new filter is equivalent to the conventional f-k dip filter in multiple suppression for simple situations. However, when the multiples and primaries are mixed in the same quadrant and have only slight difference in dip, the new filter offers significant advantages over the conventional technique.

A new interpretation of the fault-detection filter Part 2. The optimal detection filter

Abstract: Park and Rizzoni (1993) obtained closed-form expressions for detection filters; i.e. the structure of all detection filters for a given fault direction was defined. An important consequence of these results is that they permit the formation of the optimal detection filter problem, for optimization with respect to process and measurement noises. The necessary conditions for the existence of the optimal detection filter are obtained, and a numerical solution technique is shown to be feasible by virtue of the uniqueness of the detection filter gains. From an optimization point of view the problem can be regarded as optimal estimation with some structural constraints on the observer gain. This problem is solved for both the continuous-time and the discrete-time cases.

Adaptive interference canceler for narrowband and wideband interferences using higher order statistics

Abstract: A new higher order statistics-based adaptive interference canceler is introduced to mitigate narrowband and wideband interferences in environments where the interference is non-Gaussian and a reference signal, which is highly correlated with the interference, is available. The new scheme uses higher order statistics (HOS) of the primary and reference inputs and employs a gradient-type algorithm for updating the adaptive filter coefficients. The update equation of the HOS-based adaptive filter is independent of uncorrelated Gaussian noises and can mitigate the interference more effectively than adaptive filters based on second-order statistics. The performance of the. HOS-based adaptive filter is much less sensitive to the choice of the step size parameter than the adaptive filters based on the LMS algorithm. It is demonstrated, by means of extensive simulations, that the HOS-based filter can mitigate both narrowband and wideband interferences effectively. Comparisons with adaptive filters based on the LMS algorithm and second-order statistics are also presented in the paper. >

Fuzzy rule-based signal processing and its application to image restoration

Abstract: A novel signal processing technique based on fuzzy rules is proposed for estimating nonstationary signals, such as image signals, contaminated with additive random noises. In this filter, fuzzy rules concerning the relationship between signal characteristics and filter design are utilized to set the filter parameters, taking the local characteristics of the signal into consideration. The fuzzy rules are found to be quite effective, since the rules to set the filter parameters are usually expressed in an ambiguous style. The high performance of this filter is demonstrated in noise reduction of a 1-D test signal and a natural image with various training signals. >

A morphology-based filter structure for edge-enhancing smoothing

Abstract: We introduce the value-and-criterion filter structure, a new framework for designing filters based on mathematical morphology. The value-and-criterion filter structure is more flexible than the morphological structure, because it allows linear and nonlinear operations other than just the minimum and maximum to be performed on the data. One particular value-and-criterion filter, the mean of least variance (MLV) filter, finds the mean over the "subwindow" of data with the smallest variance within an overall window. The ability of the MLV filter to smooth noise while preserving and enhancing edges and corners is demonstrated. An example application of the MLV filter in improving the contrast of magnetic resonance images is also shown. >

New filters for internal model control design

Abstract: In this paper we study the design of a new two-degree-of-freedom filter for the internal model control (IMC) method. The new filter alleviates some disadvantages of the standard IMC filter when the IMC method is applied to unstable plants that do not have non-minimum-phase zeros. We show that by employing the new filter, the resulting system has a flatter frequency response, better stability robustness, and little overshoot in the step response. Furthermore, one of its design parameters can be related directly to the closed-loop bandwidth and the other parameter can be used to control the recovery time after an overshoot has occurred in the step response. These features are important in the application of the IMC method to a new approach of adaptive robust control. Examples are given in the paper to illustrate the new filter design.

Method for adaptively filtering doppler signals using a complex time domain filter

Abstract: A time domain technique for implementing an adaptive wall filter improves imaging of low-velocity blood flow by removing signals associated with slowly moving tissue. Adaptive wall filtering is performed by estimating wall velocity and bandwidth, and then filtering the basebanded data with a complex time domain notch filter. The wall velocity estimate determines the center frequency of a wall signal while the wall variance estimate determines the wall signal bandwidth. The complex filter coefficients selected are those which will center the complex notch filter on the wall center frequency, and which will set the filter cutoff frequencies (measured from this center frequency) to match the wall signal bandwidth.

Adaptive control method for periodic signal

Abstract: PROBLEM TO BE SOLVED: To properly cope with changes of external conditions of a controlled system, etc., and to perform control with high convergence stability at low cost by starting the data update of an estimation transfer function when the update value, etc., of a filter coefficient becomes larger than a reference value and updating filter coefficieints alternately by an adaptive filter. SOLUTION: An adaptive control part of e.g. an automobile is provided with a frequency decision part 31, an adaptive filter W32, the transfer function 34 of a controlled system, and an update adaptive filter 35 which updates the adaptive filter W32. On a signal input side, the estimation transfer function 36 is provided in parallel to the adaptive filter 32 and its output side is connected to the update adaptive filter W35. In this configuration, the data update of the estimation transfer function 35 is performed when the update value or mean value of the filter coefficient becomes larger than the reference value in the update period of the filter coefficient by the adaptive filter W32. Further, the update of data of the estimation transfer function 36 and the update of the filter coefficient by the adaptive filter W32 are performed alternately at specific time intervals.

Method of and apparatus for identifying a system with adaptive filter

Abstract: A method of and an apparatus for identifying a system which allow a filter coefficient to be updated accurately even if noise is mixed. The apparatus for identifying a system includes an adaptive filter for processing a reference input signal to produce an output signal, a subtractor for subtracting the output signal of the adaptive filter from an observed signal, a power estimating circuit for estimating the power of the reference input signal, and a step size determining circuit for determining a step size based on the estimated power of the reference input signal. The step size determining circuit generates a step size according to a function of the power of the reference input signal which monotonously increases if the power of the reference input signal is smaller than a threshold and monotonously decreases if the power of the reference input signal is greater than the threshold.

Color adaptive frame averaging

Abstract: A color adaptive frame averaging method for an ultrasound imaging system adds persistence to images. The color adaptive frame averaging is achieved by computing filter weighting coefficients and using the filter weighting coefficients to compensate for aliased color data. Frame rate compensation is achieved by adjusting the filter weighting coefficients. In accordance with the present invention, the color adaptive frame averaging method comprises a filter, such as an infinite impulse response filter.