Showing papers on "Filter design published in 1996"

Exponential state space filters: a generic current mode-design strategy

Abstract: A new method of analog filter design is proposed where nonlinear active components are a natural part of a filter realizing an overall linear transfer function. This approach to design is articulated in the generation of the class of so-called "Exponential State Space" (ESS) filters. An outgrowth of "log filters", ESS filters are created via a mapping on the state space of a linear filter. Specifically, the state variables are equal to simple functions of exponentials or node voltages. The use of exponential, hyperbolic tangent, and hyperbolic sine mappings is shown to produce realizable nodal equations that result in "log", "tanh" and "sinh" filters, respectively. Aspects of interpretation and realization of the transformed state equations are discussed. It is shown that sinh filters are class AB filters, which is an intriguing extension of a concept introduced by Seevinck (1990). The different filter types are compared to an analogous standard transconductance-C filter via simulation of a band-pass filter with a Q of 5. All filters demonstrate tunability over a 100 to 1 range with excellent frequency response stability and accuracy over the tuning range, which extends to 5 MHz. These results and IMD and noise performance are given using both ideal transistors and transistors whose cutoff frequency equals approximately 300 MHz.

Differential evolution design of an IIR-filter

Abstract: The task of designing an 18 parameter IIR-filter (IIR=infinite impulse response) which has to meet tight specifications for both magnitude response and group delay is investigated. This problem is usually tackled by specialized design methods and requires an expert in digital signal processing for its solution. The use of the general purpose minimization method differential evolution (DE), however, allows filter design with a minimum knowledge of digital filters.

Optimal Surface Smoothing as Filter Design

Abstract: Smooth surfaces are approximated by polyhedral surfaces for a number of computational purposes. An inherent problem of these approximation algorithms is that the resulting polyhedral surfaces appear faceted. Within a recently introduced signal processing approach to solving this problem [7, 8], surface smoothing corresponds to low-pass filtering. In this paper we look at the filter design problem in more detail. We analyze the stability properties of the low-pass filter described in [7, 8], and show how to minimize its running time. We show that most classical techniques used to design finite impulse response (FIR) digital filters can also be used to design significantly faster surface smoothing filters. Finally, we describe an algorithm to estimate the power spectrum of a signal, and use it to evaluate the performance of the different filter design techniques described in the paper.

Input filter design for power factor correction circuits

Abstract: The issues involved in the design of power factor correction circuit input filters are significantly different from those involved in the design of input filters for DC-DC power converters. In many cases, the EMI and power factor requirements are impossible to meet using the existing filtering technology. This paper proposes the use of high-order elliptic filters to achieve the required EMI attenuation and power factor. The new input filter technology provides a significant filter size reduction over the standard filter designs, minimizes the filter-power converter interaction, and maintains a good converter power factor. New active and passive filter damping methods that guarantee optimal filter pole damping, while virtually eliminating damping resistor power dissipation, are proposed. The filter design procedure that makes possible a simple and fast design of filters with an arbitrary number of stages is also presented.

Low-rank adaptive filters

Abstract: We introduce a class of adaptive filters based on sequential adaptive eigendecomposition (subspace tracking) of the data covariance matrix. These new algorithms are completely rank revealing, and hence, they can perfectly handle the following two relevant data cases where conventional recursive least squares (RLS) methods fail to provide satisfactory results: (1) highly oversampled "smooth" data with rank deficient of almost rank deficient covariance matrix and (2) noise-corrupted data where a signal must be separated effectively from superimposed noise. This paper contradicts the widely held belief that rank revealing algorithms must be computationally more demanding than conventional recursive least squares. A spatial RLS adaptive filter has a complexity of O(N/sup 2/) operations per time step, where N is the filter order. The corresponding low-rank adaptive filter requires only O(Nr) operations per time step, where r/spl les/N denotes the rank of the data covariance matrix. Thus, low-rank adaptive filters can be computationally less (or even much less) demanding, depending on the order/rank ratio N/r or the compressibility of the signal. Simulation results substantiate our claims. This paper is devoted to the theory and application of fast orthogonal iteration and bi-iteration subspace tracking algorithms.

FIR filter design via semidefinite programming and spectral factorization

Abstract: We present a semidefinite programming approach to FIR filter design with arbitrary upper and lower bounds on the frequency response magnitude. It is shown that the constraints can be expressed as linear matrix inequalities (LMIs), and hence they can be easily handled by interior-point methods. Using this LMI formulation, we can cast several interesting filter design problems as convex or quasi-convex optimization problems, e.g. minimizing the length of the FIR filter and computing the Chebychev approximation of a desired power spectrum or a desired frequency response magnitude on a logarithmic scale.

Improved Filter Design in Internal Model Control

Abstract: The widely published internal model control (IMC) proportional-integral-derivative (PID) tuning rules provide poor load disturbance suppression for processes in which the desired closed-loop dynamics is significantly faster than the open-loop dynamics. The IMC filter is modified to derive low-order controllers that provide effective disturbance suppression irrespective of the location at which the disturbances enter the closed-loop system.

System for adaptively filtering audio signals to enhance speech intelligibility in noisy environmental conditions

Abstract: A method and system are provided for adaptively reducing noise in frames of digitized audio signals that include both speech and background noise. Frames of digitized audio signals are passed through an adjustable, high-pass filter circuit to filter a portion of background noise located in a low frequency range of the digitized signal. The filter circuit is adjusted by a filter control circuit adapted for a current frame to exhibit a selected frequency response curve. The filter control circuit includes a speech detector for detecting the presence or absence of speech in the frames of digitized audio signals. The filter circuit is adjusted when no speech is detected in the current frame. In a first preferred embodiment, the filter control circuit controls the filter circuit by calculating a noise estimate corresponding to the background noise, and adjusting the filter circuit based on the noise estimate. As the noise estimates increase, the filter circuit is adjusted to extract increasing amounts of energy falling in low frequency ranges of speech. In a second preferred embodiment, the filter circuit is adjusted as a function of a noise profile estimate. A noise profile estimate for a current frame is determined as a function of speech detection and is compared to a reference noise profile. Based on this comparison, the filter circuit is adaptively adjusted.

Low-power digital filtering using approximate processing

Abstract: We present an algorithmic approach to the design of low-power frequency-selective digital filters based on the concepts of adaptive filtering and approximate processing. The proposed approach uses a feedback mechanism in conjunction with well-known implementation structures for finite impulse response (FIR) and infinite impulse response (IIR) digital filters. Our algorithm is designed to reduce the total switched capacitance by dynamically varying the filter order based on signal statistics. A factor of 10 reduction in power consumption over fixed-order filters is demonstrated for the filtering of speech signals.

On the Security of Nonlinear Filter Generators

Abstract: By regarding a nonlinear filter keystream generator as a finite input memory combiner, it is observed that a recent, important attack introduced by Anderson can be viewed as a conditional correlation attack. Necessary and sufficient conditions for the output sequence to be purely random given than the input sequence is such are pointed out and a new, so-called inversion attack is introduced, which may work for larger input memory sizes in comparison with the Anderson's attack. Large input memory size and use of full positive difference sets and correlation immune nonlinear filter functions are proposed as new design criteria to ensure the security against the considered attacks.

Constrained least square design of FIR filters without specified transition bands

Abstract: This paper puts forth the notion that explicitly specified transition bands have been introduced in the filter design literature in part as an indirect approach for dealing with discontinuities in the desired frequency response. We suggest that the use of explicitly specified transition bands is sometimes inappropriate because to satisfy a meaningful optimality criterion, their use implicitly assumes a possibly unrealistic assumption on the class of input signals. This paper also presents an algorithm for the design of peak constrained lowpass FIR filters according to an integral square error criterion that does not require the use of specified transition bands. This rapidly converging, robust, simple multiple exchange algorithm uses Lagrange multipliers and the Kuhn-Tucker conditions on each iteration. The algorithm will design linear- and minimum-phase FIR filters and gives the best L/sub 2/ filter and a continuum of Chebyshev filters as special cases. It is distinct from many other filter design methods because it does not exclude from the integral square error a region around the cut-off frequency, and yet, it overcomes the Gibbs' phenomenon without resorting to windowing or 'smoothing out' the discontinuity of the ideal lowpass filter.

The theory and design of arbitrary-length cosine-modulated filter banks and wavelets, satisfying perfect reconstruction

Abstract: It is well known that FIR filter banks that satisfy the perfect-reconstruction (PR) property can be obtained by cosine modulation of a linear-phase prototype filter of length N=2mM, where M is the number of channels. In this paper, we present a PR cosine-modulated filter bank where the length of the prototype filter is arbitrary. The design is formulated as a quadratic-constrained least-squares optimization problem, where the optimized parameters are the prototype filter coefficients. Additional regularity conditions are imposed on the filter bank to obtain the cosine-modulated orthonormal bases of compactly supported wavelets. Design examples are given.

Distance-classifier correlation filters for multiclass target recognition.

Abstract: We describe a correlation-based distance-classifier scheme for the recognition and the classification of multiple classes. The underlying theory uses shift-invariant filters to compute distances between the input image and ideal references under an optimum transformation. The original distance-classifier correlation filter was developed for a two-class problem. We introduce a distance-classifier correlation filter that simultaneously considers multiple classes, and we show that the earlier two-class formulation is a special case of the classifier presented. Initial results are presented to demonstrate the discrimination- and distortion-tolerance capabilities of the proposed filter.

A fast least-squares algorithm for linearly constrained adaptive filtering

Abstract: An extension of the field of fast least-squares techniques is presented. It is shown that the adaptation gain, which is updated with a number of operations proportional to the number of transversal filter coefficients, can be used to update the coefficients of a linearly constrained adaptive filter. An algorithm that is robust to round-off errors is derived. It is general and flexible. It can handle multiple constraints and multichannel signals. Its performance is illustrated by simulations and compared with the classical LMS-based Frost (1972) algorithm.

FIR filter design for frequency invariant beamformers

Abstract: Two methods of implementing FIR filters for a frequency invariant beamformer are presented. Each of these methods uses a single underlying set of filter coefficients obtained directly from the desired beamformer response. One method uses multirate processing, and the other is based on a single sampling rate.

Log domain filtering for RF applications

Abstract: A new second-order log filter topology, which is particularly useful for RF signal processing, is introduced with a discussion of how its features meet the needs of RF design. The design concept behind log filters is reviewed. Simulation and experimental results on a test IC are presented for an electronically tunable filter which operates beyond 400 MHz, with Q's in excess of 60, using the AT&T CBIC-V2 process.

Gabor filter design for multiple texture segmentation

Abstract: A method is presented for the design of a single Gabor filter for the segmentation of multitextured images. Earlier methods were limited to filters designed for one or two textures or to filters selected from a predetermined filter bank. Our proposed method yields new insight into the design of Gabor filters for segmenting multitextured images and lays an essential foundation for the design of multiple Gabor filters. In the method, Rician statistics of filtered textures at two different Gabor-filter envelope scales are used to efficiently generate probability density estimates for each filtered texture over an extensive set of candidate filter parameters. Variable degrees of postfiltering and the accompanying effect on postfilter output statistics are also included in the design procedure. The result is a unified framework that analytically relates the texture power spectra, Gabor-filter parameters, postfiltering effects, and image-segmentation error. Finally, the resulting filter design is based on all constituent textures and is not constrained to a limited set of candidate filters.

A comprehensive evaluation of filters for radar speckle suppression

Abstract: This paper presents the result of a comprehensive evaluation of filters for radar speckle suppression. Seven filters in the Radar Module of Erdas/IMAGINE(R) were evaluated, including the mean filter, the median filter, the Lee-sigma filter, the local region filter, the Lee filter, the Frost filter, and the MAP (maximum a posteriori) filter. The performance of these filters was measured in terms of five criteria: speckle suppression index, edge enhancing index, feature preserving index (for both linear features and point features), image detail preserving coefficient, and speckle image analysis. Visual effect of filtered image and its filter theoretical basis were discussed. The relationship between filter performance and speckle patterns was also examined.

Synthesis of coherent two-port optical delay-line circuit with ring waveguides

Abstract: A method has already been reported by the author and others for synthesizing coherent two-port lattice-form optical delay-line circuits which have the same filter characteristics as finite impulse response (FIR) digital filters. This paper proposes a two-port circuit configuration with ring waveguides which can realize the same filter characteristics as infinite impulse response (IIR) digital filters. It also describes a synthesis method for realizing arbitrary IIR filter characteristics with the circuit configuration. This method is based on scattering matrix factorization. Some synthesis examples are demonstrated including an elliptic filter, a Butterworth filter, an optical filter with maximally flat group-delay characteristics, a group-delay dispersion equalizer, and a multichannel selector.

A filter design technique for steerable pyramid image transforms

Abstract: We describe a novel recursive filter design technique for multi-scale "pyramid" transforms. The recursion in the design technique follows that of the pyramid construction, and allows us to solve a reduced design problem at each step. We demonstrate the use of this technique by designing filters of various orientation bandwidths for use in a "steerable pyramid" image transform.

Novel universal voltage-mode biquad filter with three inputs and one output using only two current conveyors

Abstract: A new universal voltage-mode second-order filter with three inputs and one output employing two current conveyors, two capacitors and three resistors is presented. With the same number of passive elements, the new filter employs one less current conveyor than the latest published paper. Also, the new filter does not need a voltage follower. The new circuit still offers the following advantageous features of the published filter of this category: realization of all-pass, notch, high-pass, bandpass and low-pass signals from the same configuration, no requirements for component-matching conditions, orthogonal control of ω0 and Q, low active and passive sensitivities.

Local adaptive image restoration and enhancement with the use of DFT and DCT in a running window

Abstract: On the base of local criteria of processing quality, a class of local adaptive linear filters for image restoration and enhancement is introduced. The filters work in a running window in the domain of DFT of DCT and have O (size of the window) computational complexity thanks to recursive algorithms of running DFT and DCT. The filter design and the recursive computation of running DCT are outlined and filtering for edge preserved noise suppression, blind image restoration and enhancement is demonstrated.

Method and apparatus for estimating a cognitive decision made in response to a known stimulus from the corresponding single-event evoked cerebral potential

Abstract: The present invention estimates the cognitive decision made in response to a known stimulus from the corresponding single-event evoked cerebral potential. The present invention uses a unique recursive procedure to identify the decision from a mathematical description of the potential as the output of a cerebrally located, autoregressive, moving average filter with the stimulus as an exogenous input. The procedure employs in a two-step sequence, the least squares algorithm to update the filter coefficients, followed by a Taylor's Series approximation for updating an internal cerebral source signal which is generated in response to the external stimulus. The recursive procedure computes the attenuation used by the moving average component of the filter to produce the cerebral source signal. This procedure is repeated for all feasible cerebral source signals, computed from the set of possible event evoked average response potentials, to produce a set of attenuator-values. These values are then used as input to a multiple-layered, feed-forward artificial neural network for identifying the decision made from the set of feasible responses. In turn, the power spectrum computed from the autoregressive coefficients is used to track the cognitive state and therefore the reliability of the decision estimate. The present invention may be used for the control by mental thought of computerized visual and aural display functions, by measuring the electroencephalogram in time with the operant orientation of the user onto a displayed stimulus.

A general planar waveguide autoregressive optical filter

Abstract: A general architecture for an autoregressive (AR) planar waveguide optical filter is demonstrated for the first time. Its advantages are a flatter passband, sharper rolloff and better rejection in the stopband compared to finite impulse response (FIR) filters with the same number of stages. The architecture can be extended to an arbitrary number of stages. A modified Levinson algorithm is derived for filter synthesis and analysis which includes waveguide loss and phase errors between stages. The filter analysis algorithm allows the filter's coupling ratios and phase errors for each stage to be determined from the filter's spectral response. When combined with a postfabrication tuning process, this analysis method provides feedback for optimizing the response. Autoregressive lattice filters were designed and fabricated using Ge-doped silica waveguides. Measurements are reported which demonstrate the synthesis and analysis algorithms. The impact of fabrication tolerances on filter synthesis and of measurement uncertainties on filter analysis are investigated.

Image decoder using adjustable filtering

Abstract: Noise contained in a reproducing image signal is suppressed by performing a filtering operation on an image signal obtained by decoding data that has been coded with a unit of a block consisting of m×n pixels. A filter circuit having a plurality of filter characteristics suppresses noise, and a characteristics selection circuit switches the filter characteristics of the filter circuit by use of a quantizing parameter employed for coding the image signal.

Multirate receive device and method using a single adaptive interpolation filter

Abstract: A device for receiving a source digital signal transmitted at one or more source symbol frequencies Fs samples a received analog signal transposed into the baseband and delivers an entirely demodulated sample signal. The sampling frequency Fe complies with the generalized sampling condition. A single filter module filtering the sampled signal comprises a digital filter controlled by a filter coefficient vector. The filter coefficients are determined according to a determination criterion allowing for the ratio of the sampling frequency Fe to the source frequency Fs, to interpolate the sampled signal, and for an analysis of the transmission path, in order to limit interference introduced by the path.