This paper discusses the relationship between the zero crossings or zeros of band-limited signals and their nonlinear transformations. It is proved that the bandwidth of a signal can be compressed by a ratio of 1/ n i...
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This paper discusses the relationship between the zero crossings or zeros of band-limited signals and their nonlinear transformations. It is proved that the bandwidth of a signal can be compressed by a ratio of 1/ n if and only if the signal has n th-order zero crossings or zeros (if complex). Also, a monotonic nonlinearity in the observation of a band-limited signal can be identified from the zero crossings (or zeros) of the derivative of the observed signal. (The results are for one-dimensional signals. Extensions to two-dimensional signals remain to be addressed.)
A new algorithm for ray tracing parametric surface patches is presented. The method uses quasi-Newton iteration to solve for the ray/surface intersection and utilizes ray-to-ray coherence by using numerical informatio...
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Factor inverse matched filtering (FIMF) and factor inverse filtering (FIF) are signal processing techniques used to obtain desired signal responses. Both are especially useful procedures for ‘‘pulse‐compression’’...
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Factor inverse matched filtering (FIMF) and factor inverse filtering (FIF) are signal processing techniques used to obtain desired signal responses. Both are especially useful procedures for ‘‘pulse‐compression’’ processing and channel measurements. The theory is developed for a simple channel and known noise power spectral density so that comparison may be made with matched filtering. Expressions for the pulse‐compression energy gain, nonflatness loss NFL, and total performance are derived. The NFL is useful in selecting the best among practical pulse‐compression modulations, and with FIMF and FIF, has been used extensively since 1974 by the authors and their co‐workers in underwater acoustic propagation measurements and ocean acoustictomography.
A layer stripping procedure for solving three‐dimensional Schr?dinger equationinverse scattering problems is developed. This procedure operates by recursively reconstructing the Radon transform of the potential from ...
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A layer stripping procedure for solving three‐dimensional Schr?dinger equationinverse scattering problems is developed. This procedure operates by recursively reconstructing the Radon transform of the potential from the jump in the Radon transform of the scattered field at the wave front. This reconstructed potential is then used to propagate the wave front and scattered field differentially further into the support of the potential. The connections between this differential procedure and integral equation procedures are then illustrated by the derivations of two well known exact integral equation procedures using the Radon transform and a generalized Radon transform. These procedures, as well as the layer stripping procedure, are then reduced to the familiar Born approximation result for this problem by neglecting multiple scattering events. This illustrates the central role of the Radon transform in both exact and approximate inversion procedures.
This paper describes a technique for the enhancement of images by FIR filters which compensates for the decreased response of human vision at high spatial frequencies. Because many images contain mainly horizontal and...
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This paper describes a technique for the enhancement of images by FIR filters which compensates for the decreased response of human vision at high spatial frequencies. Because many images contain mainly horizontal and vertical features, and because vision is less acute along diagonals, it is possible to design anisotropic enhancement filters which do not increase greatly the background noise. The anisotropic design methodology also incorporates other results on filter design based on human vision which have recently been reported by the author and coworkers.
We propose a new, robust pitch detection algorithm for speech degraded by additive noise. Our algorithm exploits the high correlation between adjacent pitch periods that does not exist for the segment as a whole and p...
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We propose a new, robust pitch detection algorithm for speech degraded by additive noise. Our algorithm exploits the high correlation between adjacent pitch periods that does not exist for the segment as a whole and performs well in the vicinity of voiced/unvoiced regions where the local SNR is low. The algorithm works as follows. We first determine an estimate of the pitch period near the short time peak energy where the local SNR is highest. We then adaptively estimate the local pitch period from the peak towards the transition region by using pitch synchronous cross-correlation with an updated waveform. The performance of this new algorithm is compared to the SIFT and CEPSTRUM algorithms.
A comprehensive analysis of the mean-square learning characteristics of stochastic-descent algorithms is presented. The approach is based on the commonly exploited simplifying assumption of stationary independent trai...
A comprehensive analysis of the mean-square learning characteristics of stochastic-descent algorithms is presented. The approach is based on the commonly exploited simplifying assumption of stationary independent training vectors. Characteristics analyzed include stability, steady-state misadjustment, initial rate of convergence, optimum step size, and steady-state autocovariance and spectral characteristics of the weight-vector. Effects on these characteristics due to degree of randomness of stochastic gradient, particular data distribution, and data corruption are isolated and analyzed. An objective of the work is to keep the number of simplifying assumptions and approximations to a minimum. Comparison of results with previous more approximate analyses are made. Lernkurven von stochastischen Gradienten Algorithmen werden untersucht. Die vereinfachende Annahme von stationären, unabhängigen Trainingsvektoren wird benutzt. Charakteristiken die untersucht werden beinhalten Stabilität, ‘steady state’ Fehlanpassung, Start Konvergenz, optimaler Schritt sowie ‘steady state’ Autokovarianz und spektrale Charakteristik des Gewichtsvektors. Die Effekten auf diese Charakteristiken von dem Zufälligkeitsgrad des stichastischen Gradienten, besonderer Daten Verteilung und Daten Verderbung werden isoliert und analysiert. Ein Zielpunkt dieser Arbeit ist es die Anzahl vereinfachenden Annahmen und Approximationen auf ein minimum zu beschränken. Vergleiche mit Resultaten die von approximativeren Analysen stammen werden gezogen. Une analyse d'ensemble des caractéristiques de convergence de l'erreur quadratique moyenne dans les algorithmes utilisant la décroissance du gradient stochastique est presentée. Cette approche est basée sur l'hypothése simplificatrice classique de stationnarité et indépendance des vecteurs de test. Les caractéristiques analysées comprennent la stabilité, l'écart d'état stable, la vitesse initiale de convergence, le pas optimum d'incrémentation, et l'autocovarian
A study aimed at segmenting a high-resolution black and white image of Sunnyvale, California, is described. In this study regions were classified as belonging to any one of nine classes: residential, commercial/indust...
A study aimed at segmenting a high-resolution black and white image of Sunnyvale, California, is described. In this study regions were classified as belonging to any one of nine classes: residential, commercial/industrial, mobile home, water, dry land, runway/taxiway, aircraft parking, multilane highway, and vehicle parking. The classes were selected so that they directly relate to the Defense Mapping Agency's Mapping, Charting and Geodesy tangible features. To attack the problem a statistical segmentation procedure was devised. The primitive operators used to drive the segmentation are texture measures derived from cooccurrence matrices. The segmentation procedure considers three kinds of regions at each level of the segmentation: uniform, boundary, and unspecified. At every level the procedure differentiates uniform regions from boundary and unspecified regions. In the assigns a class label to the uniform regions. The boundary and unspecified regions are split to form higher level regions. The methodologies involved are mathematically developed as a series of hypothesis tests. While only a one-level segmentation was performed studies are described which show the capabilities of each of these hypothesis tests. In particular an 83% correct classification was obtained in testing the labeling procedure. These studies indicate that the proposed procedure should be useful for land use classifications as well as other problems.
The well-known advantages of pipelining as applied to Finite Impulse Response (FIR) Residue Number System (RNS) arithmetic digital filters is extended to the important area of Infinite Impulse Response (IIR) digital f...
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The well-known advantages of pipelining as applied to Finite Impulse Response (FIR) Residue Number System (RNS) arithmetic digital filters is extended to the important area of Infinite Impulse Response (IIR) digital filters through a new technique based on augmentation of the IIR transfer function. Through this technique, pipelined IIR filters based on RNS Read-Only-Memory (ROM) table look-up techniques can be designed which offer throughput rates equal to the table look-up time of the ROM's. This high-speed realization can be achieved even though the recursive filter algorithm requires multiple delays in realizing the output of the filter. For the example of a typical second-order IIR filter, the pipelined structure represents a five-fold increase in speed over standard techniques. Higher order realizations will yield proportionately higher speed improvements. Although the new technique does increase somewhat the hardware complexity of the filter, the increase in speed will often justify the additional hardware. The paper discusses the basic technique, stability considerations, and hardware realizations.
Accurate and reliable detection of unique objects is an important component of an image understanding system. The objects are considered to have a unique pattern and should be recognized based upon their own character...
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