An approach to time-domain pitch detection based on the concepts of center of mass is presented and evaluated. Excursions, or bumps, in speech signals are treated as geometric areas and replaced by their total mass lu...
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An approach to time-domain pitch detection based on the concepts of center of mass is presented and evaluated. Excursions, or bumps, in speech signals are treated as geometric areas and replaced by their total mass lumped at the centers of mass. Intervals between masses are grouped into candidate classes. Coincidence and coherence indices of these classes are computed to determine the most likely pitch estimate. Postprocessing consists of a simple error-correction and silence-detection scheme. This algorithm compares favourably in performance with the autocorrelation method, using pitch contours from electroglottograph signals as a reference. The algorithm is tested in noisy environments simulated by uniformly distributed white noise and multitalker babble noise. Results show that the algorithm is robust and accurate. The implementation of this algorithm for a vibrotactile device to aid lipreading is described.< >
Experimental analyses of an implementation of an SIMD algorithm for recursive digital filtering using the partitionable SIMD/MIMD (PASM) parallel processing system prototype at Purdue University are presented. The alg...
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Experimental analyses of an implementation of an SIMD algorithm for recursive digital filtering using the partitionable SIMD/MIMD (PASM) parallel processing system prototype at Purdue University are presented. The algorithm used easily generalizes to use N processing elements (PEs). Timing-based analyses are made based on a four-PE version by examining the following constituent execution times: microcontroller execution time, PE execution time, broadcast communication time, and the execution time of five additional phases in the recursive digital filtering summation calculation. Broadcast execution time was found to account for roughly 44% of the total execution time, and the implication of this is discussed for larger problem sizes and machine sizes. The total measured execution time is verified through summation of execution times for the various components of the algorithm.< >
In ocean acoustic tomography, maximal length binary shift- register sequences, m-sequences, are used to modulate acoustic carriers to achieve high average power and good time and Doppler resolution. To date, the under...
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In ocean acoustic tomography, maximal length binary shift- register sequences, m-sequences, are used to modulate acoustic carriers to achieve high average power and good time and Doppler resolution. To date, the underwater transmitters and receivers have been in fixed positions, and signal processing has consisted of demodulation followed by factor inverse filtering. Ocean tomography now is being extended to include the use of moving, ship-towed, transmitters and receivers, where signal processing must account for Doppler time and frequency resealing. This paper describes the signal demodulation and processing methods developed for moving ship tomography and presents illustrative results.
A new deflected stochastic-gradient algorithm for adaptive sensor arrays is introduced. It is shown to have the capability of converging substantially faster than the nondeflected stochastic gradient (LMS) algorithm b...
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A new deflected stochastic-gradient algorithm for adaptive sensor arrays is introduced. It is shown to have the capability of converging substantially faster than the nondeflected stochastic gradient (LMS) algorithm but slower than the recursive least squares (RLS) algorithm. Because of its amenability to reduction of computational complexity by data quantization, it has the potential for processing digital signals with bandwidths one to two orders of magnitude larger than the bandwidths manageable with the RLS algorithm for sensor arrays containing a number of adjustable weights in the approximate range of 10-50.
The importance of the concept of cyclostationarity in design and analysis of signal detectors, synchronizers, and extractors in communication systems is briefly discussed, and the central role of spectral correlation,...
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The importance of the concept of cyclostationarity in design and analysis of signal detectors, synchronizers, and extractors in communication systems is briefly discussed, and the central role of spectral correlation, in the characterization of random processes that are cyclostationary in the wide sense, is explained. A spectral correlation function that is a generalization of the power spectral density function is described, and a corresponding generalization of the Wiener-Khinchine relation and several other fundamental spectral correlation relations also are described. Explicit formulas for the spectral correlation function for various types of analog-modulated signals are derived. This includes pulse and carrier amplitude modulation, quadrature amplitude carrier modulation, and phase and frequency carrier modulation. To illustrate the differing spectral correlation characteristics of different modulation types, the magnitudes of the spectral correlation functions are graphed or described in graphical terms as the heights of surfaces above a bifrequency plane.
As a continuation of Part I, the spectral correlation function is presented for a variety of types of digitally modulated signals. These include digital pulse-amplitude, pulse-width, and pulse-position modulation, and...
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As a continuation of Part I, the spectral correlation function is presented for a variety of types of digitally modulated signals. These include digital pulse-amplitude, pulse-width, and pulse-position modulation, and various types of phase-shift keying and frequency-shift keying. The magnitudes of the spectral correlation functions are graphed as the heights of surfaces above a bifrequency plane, and these graphs are used as visual aids for comparison and contrast of the spectral correlation properties of different modulation types.
Upper and lower bounding first-order linear recursions for the mean-squared error realized with the LMS algorithm subjected to a sequence of independent nonstationary training vectors are derived. These bounds coincid...
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Upper and lower bounding first-order linear recursions for the mean-squared error realized with the LMS algorithm subjected to a sequence of independent nonstationary training vectors are derived. These bounds coincide to give the exact evolution of mean-squared error for the problem of identification of a nonrecursive time-varying system with white-noise excitation. This leads to an exact formula for time-averaged mean-squared error that is used to study optimization of the step-size parameter for minimum time-average misadjustment. New results on dependence of the minimal step size and the minimum misadjustment on the degree of nonstationarity are obtained.
An algorithm is presented which can be used to compute a temporally adaptive, recursive solution to the problem of estimating the linear prediction parameters of speech. The method is theoretically equivalent to conve...
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An algorithm is presented which can be used to compute a temporally adaptive, recursive solution to the problem of estimating the linear prediction parameters of speech. The method is theoretically equivalent to conventional adaptive sequential regression, but is slightly more efficient and computationally much more straightforward. Application to the problem of recognition of speech of the profoundly disabled is discussed.
The inverse problem of reconstructing the resistivity of the earth, varying both laterally and with depth, from direct current measurements is considered. The problem is formulated as a multidimensional inverse scatte...
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The inverse problem of reconstructing the resistivity of the earth, varying both laterally and with depth, from direct current measurements is considered. The problem is formulated as a multidimensional inverse scattering problem and solved using a layer stripping algorithm. This algorithm recursively reconstructs the resistivity and electrical potential on horizontal planes of increasing depth by downward continuation. This is the first exact solution to the inverse resistivity problem for resistivity varying laterally as well as with depth. The algorithm is an extension of an algorithm proposed by Levy for resistivity varying in one dimension.
A fast algorithm for recovering profiles of density and compressional (P) and shear-vertical (SV) wave speeds as functions of depth for the inverse seismic problem in a continuous layered elastic medium is obtained. T...
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A fast algorithm for recovering profiles of density and compressional (P) and shear-vertical (SV) wave speeds as functions of depth for the inverse seismic problem in a continuous layered elastic medium is obtained. This algorithm differs from previous fast algorithms for this problem since it requires only the compressional wave P-P reflection response at the surface of the medium, for three different slownesses or angles of incidence. Previous algorithms have required shear stress data in the form of the P-SV and SV-SV reflection responses, making them unsuitable for an ocean environment. This algorithm is thus much more suitable for reconstructing the ocean floor from pressure data taken in the ocean. The algorithm is exact, and it includes the effects of multiple reflections and mode conversions. A computer run illustrates the performance of the algorithm on synthetic data.
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