Showing papers on "Multidimensional signal processing published in 1990"

On a simple algorithm to calculate the 'energy' of a signal

Abstract: A simple algorithm is derived that permits on-the-fly calculation of the energy required to generate, in a certain sense, a signal. The results of applying this algorithm to a number of well-known signals are shown. Some of the invariance and noise properties of the algorithm are derived and verified by simulation. The implementation of the algorithm and its application to speech processing are briefly discussed. >

Morphological systems for multidimensional signal processing

Abstract: The basic theory and applications of a set-theoretic approach to image analysis called mathematical morphology are reviewed. The goals are to show how the concepts of mathematical morphology geometrical structure in signals to illuminate the ways that morphological systems can enrich the theory and applications of multidimensional signal processing. The topics covered include: applications to nonlinear filtering (morphological and rank-order filters, multiscale smoothing, morphological sampling, and morphological correlation); applications to image analysis (feature extraction, shape representation and description, size distributions, and fractals); and representation theorems, which shows how a large class of nonlinear and linear signal operators can be realized as a combination of simple morphological operations. >

Analog & digital signal processing

Abstract: The Fourier series in spectral analysis and function approximation the Fourier transformation and generalized signals the Laplace transformation and some of its applications analogue signal processing systems digitization of analogue signals discrete signals and systems design of digital filters the fast fourier transform and its applications stochastic signals and power spectra finite word-length effects in digital signal processors linear estimation and adaptive filtering.

Algorithm-based fault detection for signal processing applications

Abstract: The increasing demands for high-performance signal processing along with the availability of inexpensive high-performance processors have results in numerous proposals for special-purpose array processors for signal processing applications. A functional-level concurrent error-detection scheme is presented for such VLSI signal processing architectures as those proposed for the FFT and QR factorization. Some basic properties involved in such computations are used to check the correctness of the computed output values. This fault-detection scheme is shown to be applicable to a class of problems rather than a particular problem, unlike the earlier algorithm-based error-detection techniques. The effects of roundoff/truncation errors due to finite-precision arithmetic are evaluated. It is shown that the error coverage is high with large word sizes. >

Wavelets and filter banks: relationships and new results

Abstract: The discrete version of the wavelet transform, which has recently emerged as a powerful tool for nonstationary signal analysis is closely related to filter banks, which have been studied in digital signal processing. Also, multiresolution signal analysis has been used in image processing. The relationship between these techniques is indicated. It is shown how to construct biorthogonal systems with linear-phase finite impulse response (FIR) filters and with regular analysis and synthesis. Some examples of practical interest are given. The complexity of the discrete wavelet transform is also discussed. >

Multiplier policies for digital signal processing

Abstract: The successful design of digital signal processing (DSP) systems and subsystems is often predicated on realizing fast multiplication in digital hardware. This tutorial provides the reader with a broad perspective of this important field and the pedagogy needed to understand the basic principles of digital multiplication. Both conventional and nonconventional methods of implementing multiplication, representing a mix of speed/complexity tradeoffs, are presented. Some are based on traditional shift-add structures, whereas others strive for greater mathematical sophistication. Topics include stand-alone fixed-point multipliers, cellular arrays, memory intensive policies, homomorphic systems, and modular arithmetic. >

Analog and Digital Signal Processing

Abstract: From the Publisher: Provides well balanced, detailed coverage of the techniques of signal processing in both the analog and digital domains and the ways in which they are linked in practical applications. Topics include spectral analysis of continuous and discrete signals, analysis of continuous and discrete systems and networks using transform methods, design of analog and digital filters, digitization of analog signals, power spectrum estimation of stochastic signals, the fast Fourier transform algorithms, finite word-length effects in digital signal processors and linear estimation and adaptive filtering.

Multidimensional signal processing for electro-optical target detection

Abstract: This paper describes the evolutionary development of adaptive signal processing algorithms which utilize spatial and spectral information provided by a passive infrared sensor to enhance the detectability of targets in clutter. Key parameters affecting the performance of multi-spectral detection processors are identified and discussed. Adaptive filtering algorithms are presented which can achieve near-optimum detection performance with no prior knowledge of the target and background spectral properties.© (1990) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Fast Algorithms for Signal Processing

Abstract: : Research in the area of matrix-based signal processing included matric theory, numerical and parallel computing, signal processing and a Very Large Scale Integration implementation. Results of the research are summarized in the final report with details in the publications and proceedings issued during the course of the research.

Fourier analysis and signal processing by use of the Mobius inversion formula

Abstract: A novel Fourier technique for digital signal processing is developed. This approach to Fourier analysis is based on the number-theoretic method of the Mobius inversion of series. The Fourier transform method developed is shown also to yield the convolution of two signals. A computer simulation shows that this method for finding Fourier coefficients is quite suitable for digital signal processing. It competes with the classical FFT (fast Fourier transform) approach in terms of accuracy, complexity, and speed. >

Signal processing device and method

Abstract: A signal processing device for generating an output signal corresponding to a multi-dimensional input signal such as a two-dimensional image and a method of processing such a signal. The device includes an array of processing elements which are congruent and shaped so that they can be arranged on a processing element so that adjacent pairs of elements considered as a unit are geometrically similar to each processing element. Output signals of individual processing units are linearly ordered in such a manner as to maintain adjacency of signals from adjacent processing elements in the array. The ordering facilitates one-dimensional Haar transform processing of the signals in such as a manner as to localize signal energy.

Phase retrieval using two Fourier-transform intensities

Abstract: We consider the problem of reconstructing either a one-dimensional or a two-dimensional signal from its Fourier intensity and the Fourier intensity of another signal that is related to the first by the addition of a known reference signal Several theorems are given that give conditions under which a unique reconstruction is possible, and a recursive algorithm is provided that allows for the reconstruction of the signal from the pair of Fourier intensities

Carry-save arithmetic for high-speed digital signal processing

Abstract: It is shown that carry-save arithmetic, well known from multiplier architectures, can be used for the efficient CMOS implementation of a wide variety of algorithms for high-speed digital signal processing. Existing strategies for the realization of inner-product based and recursive algorithms are recalled. New approaches are presented for carry-save implementation of decision-directed algorithms such as division, modulo multiplication, and CORDIC. >

Image processing apparatus capable of using fuzzy logic

Abstract: There is provided an image processing apparatus comprising: an input device to input an image signal; a processor for processing the input image signal and outputting an image reproduction signal; a detecting circuit to detect characteristics of the input image signal; and a control circuit to control conditions of processing of the image signal by the processor by means of a fuzzy inference based on characteristics of the image signal which were detected by the detecting circuit. Such characteristics of the image signal include the kind of image such as character, screen, and photograph. The optimum spatial filtering process can be executed for areas of each of the character, screen, and photograph types. A mixing ratio of the edge emphasis and the smoothing can be continuously changed for characteristic amounts of an original. Membership functions of a plurality of parameters are synthesized and a consequence is derived by the fuzzy inference algorithm. Thus, erroneous judgment for a vague image area is prevented and discontinuity which occurs at a change point of the image processes can be also eliminated.

Transform coding of audio signals at 64 kbit/s

Abstract: The coding of high-quality sound at 64 kb/s is of interest for applications such as ISDN. The algorithm described allows the reduction to such a bit rate while maintaining the original quality. It is based on transform coding, and uses a time-domain aliasing cancellation (TDAC) transformation. Perceptual properties and the interblock redundancy of the spectrum are involved when coding the transform coefficients. The complexity of the algorithm allows its real-time implementation on a one floating-point digital signal processor, such as the ATT DSP 32C. The performance and subjective results of the coding system are discussed. >

Adaptive digital signal processing for X-ray spectrometry

Abstract: A real-time fully digital signal processing and analyzing system based on a new concept has been developed for high count rate high resolution spectrometry The principle has been realized with digital filtering of the preamplifier output signals The system's unique features are the maximum theoretically possible throughput rate with high resolution, and the adaptive noise filtering for nearly loss-free measurements In adaptive mode the maximum output rate is about 20 times higher than in the case of the semi-Gaussian shaping, with low degradation of energy resolution All parameters of the signal processor are software controllable

Median-based algorithms for image sequence processing

Abstract: In this paper several digital video signal processing algorithms that use the median operation are presented. Both numerical and visual evaluations of the resulting image sequences clearly show that the median operation has many desirable properties for digital image sequence processing applications.© (1990) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Two dimensional fast Fourier transform converter

Abstract: A two-dimensional fast Fourier transform converter utilizes parallel digital fast Fourier transform processors and a frame serial processing path to convert two-dimensional images of large pixel count (512×512 or higher) and high dynamic range (16 bits of pixel intensity quantization) at a rate equal to or exceeding real time processing rate of 30 frames/second. The parallel processors are organized for performing the row and column transformations in a highly parallel and efficient manner. In one embodiment, a uni-directional processing path with segmented image data busses to streamline the data movement is used. In a second embodiment, a bi-directional processing path is utilized such that the fast Fourier transform processors perform row and column conversions sequentially, thus reducing by a factor of two the number of individual fast Fourier transform processors required. The converter includes three port SRAM working memories, toggled DRAM image frame storage memories, and a data transfer and sequence controller.

Fast converging subband acoustic echo cancellation using RAP on the WE DSP16A

Abstract: The application of row action projections (RAPs) to the problem of acoustic echo cancellation is discussed. It is shown how RAPs, a subset of projections onto convex sets (POCSs) and a generalization of LMS, can be used to further improve the tracking ability of subband acoustic echo canceller (SBAECs). In addition, the RAP algorithm has a useful complexity versus speed-of-convergence tradeoff. That is, RAP can use additional computational resources to speed convergence. This is used to dynamically allocate computational resources among the subband in such a way as to improve the perceptual performance of the SBAEC. The feasibility of this method is demonstrated by sizing it for AT&T's WE DSP16A digital signal processor. >

Digital voice detection apparatus and method using transform domain processing

Abstract: A waveform characterizer apparatus is disclosed for extracting cepstrum pitch and spectral properties of a waveform signal such as the baseband audio output of a receiver. The apparatus employs Fourier processing, cepstral processing, magnitude detection, logarithms processing, frequency selective filtering and time/frequency windowing to extract cepstrum pitch and spectral rolloff characteristics which can then be used to determine the signal type. One application of the invention is in a digital voice/squelch apparatus.

Blind estimation of correlated source signals

Abstract: Blind estimation of source signals is a signal extraction problem that assumes no information of the channel characteristics. In this paper, the problem of blind estimation of possibly correlated multiple source signals transmitted through a memoryless channel is investigated. In particular, our objective of blind signal estimation is to obtain fhe estimates that preserve the waveforms of the original source signals (waveform-preserving estimates). A necessary condition and two sufficient con dit ions for a c h ie v ing w a v e f o rm -p r e s e r v i ng estimation are proved. The AMUSE (Algorithm for Multiple Signal Extraction) [8] is extended so that the signal extraction can be achieved for possibly correlated sources.

Digital signal processing: efficient convolution and Fourier transform techniques

Abstract: An examination of the advanced techniques for efficiently implementing digital convolution in digital signal processing systems, this book covers the two main approaches - direct methods and Fourier transforms. Myers progressively introduces number theory and abstract algebra and his practical approach demonstrates how to use them to develop more efficient algorithms. Exercises reinforce ideas from the text and problems test the reader's understanding of these ideas.

Transform digital/optical processing system including wedge/ring accumulator

Abstract: A transform digital optical processing system generates a transform signal of an image. Fourier or other well-known transforms may be employed. The transform signal may be generated in one of two ways: optically or electronically. In optical generation a two dimensional object is generated by modulating a beam of coherent light with an image of the object. A transform image of the modulated coherent light beam is formed, using an optical transform element. The optical transform is then stored in a two dimensional buffer. The transform signal may also be generated electronically by storing a digital video image of an object and generating a Fourier or other transform of the digital video image using vector processing chips or other commercially available digital transform generating computers. This digitally generated information may be analyzed and classified through a neural network type processor. The two-dimensional transform data is then processed to obtain the inspection or other characteristics for comparison against predetermined characteristics. The two dimensional transform is divided into two types of zones, namely wedges and rings. The transform data is then mapped into a corresponding wedge and ring, and the data for each wedge and ring is accumulated or summed to obtain data values. It has been found that the summed wedge and ring data values can accurately characterize an image for inspection or other comparison purposes.

An extended fourth order blind identification algorithm in spatially correlated noise

Abstract: An eigenstructure-based method called extended fourth-order blind identification (EFOBI) is presented for the problem of blind decomposition of multiple source signals in spatially correlated noise. Estimates of the source signals and the unknown model parameters are computed by the algorithm. The method is applied to a speech enhancement problem and to the direction-of-arrival problem in array signal processing under sensor gain uncertainties and shows improved performance over traditional methods such as MUSIC. >

Multidimensional digital filtering by using parallel algorithms based on diagonal processing

Abstract: An approach for massive parallel processing in multidimensional digital filtering, which has briefly been introduced for causal digital filters in previous publications, is generalized and examined in more detail. It is based on a suitably modified sampling procedure combined with diagonal processing and does not require any additional arithmetic operations in comparison with corresponding conventional digital filtering. The condition that has to be satisfied for making the approach suitable for full parallel processing is derived. Properties of diagonal hyperplanes as required for the present approach are discussed.

Digital signal processing methods for biosequence comparison

Abstract: A method is discussed for DNA or protein sequence comparison using a finite field fast Fourier transform, a digital signal processing technique; and statistical methods are discussed for analyzing the output of this algorithm. This method compares two sequences of length N in computing time proportional to N log N compared to N2 for methods currently used. This method makes it feasible to compare very long sequences. An example is given to show that the method correctly identifies sites of known homology.

Fundamentals of multidimensional multirate digital signal processing

Abstract: This paper reviews the fundamentals of multidimensional multirate signal processing. Central to these discussions is the idea of generalized sampling-lattice. Topics discussed include nonrectangular decimators, interpolators, generalized DFT, and filter banks. The multidimensional polyphase decomposition is developed, with applications in decimation filtering and perfect reconstruction filter banks.

An analysis of subspace fitting algorithms in the presence of sensor errors

Abstract: The recently introduced class of subspace fitting algorithms for sensor array signal processing (e.g. direction-of-arrival (DOA) estimation) includes deterministic maximum likelihood, ESPRIT, weighted subspace fitting, and both one- and multidimensional MUSIC as special cases. The performance of this class of algorithms is examined for situations where the sensor array response is perturbed from its nominal value. Theoretical expressions for the error in the DOA estimates are derived and compared with several simulation examples. It is shown that in difficult cases the algorithms are especially sensitive to the choice of subspace weighting. For a particular perturbation model, and optimal subspace weighting is proposed which minimizes the DOA estimate error variance over all possible weightings when finite sample effects are neglected. >