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.
The implementation of digital filtering algorithms using pipelined vector processors is investigated. Modeling of vector processors and vectorization methods are explained, and then the performances of several impleme...
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The implementation of digital filtering algorithms using pipelined vector processors is investigated. Modeling of vector processors and vectorization methods are explained, and then the performances of several implementation methods are evaluated based on the model. Vector processor implementation of FIR filtering algorithms using the outer product method and the indirect convolution method is evaluated. Recursive and adaptive filtering algorithms, which lead to dependency problems in direct vector processor implementations, are implemented very efficiently using a newly developed vectorization method. The proposed method computes multiple output samples at a time, making the vector length independent of the filter order. Illustrative examples comparing theoretical results with Cray X-MP simulation results are included.
The phase reconstruction problem in the trispectrum domain is addressed in this correspondence. In particular, three different reconstruction algorithms are discussed and their performance is evaluated. The first two ...
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The phase reconstruction problem in the trispectrum domain is addressed in this correspondence. In particular, three different reconstruction algorithms are discussed and their performance is evaluated. The first two algorithms are recursive in nature and are shown to be sensitive to initial condition estimates.
Necessary and sufficient conditions are developed for a pair of transfer functions to have magnitude responses which sum to a constant. If, in addition, the transfer function pair is constrained to be all-pass complem...
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Necessary and sufficient conditions are developed for a pair of transfer functions to have magnitude responses which sum to a constant. If, in addition, the transfer function pair is constrained to be all-pass complementary, the transfer function pair so obtained is well suited for loudspeaker crossover applications. Such crossover systems are characterized by a pair of transfer functions which exhibit the same phase angle at all frequencies. This property has twofold implications: i) in active crossover biamplified audio systems, whereby the low frequencies and high frequencies are reproduced using separate power amplifiers, in-phase crossover transfer functions require less power in subsequent amplifier stages than other designs to achieve a given acoustic sound pressure level; and ii) the summed acoustic magnitude response is least sensitive to noncoincidental mounting of the low- and high-frequency transducers when the crossover transfer functions exhibit the same phase angle at all frequencies. The class of transfer functions realizable is quite wide, and includes squared versions of Butterworth, Chebyshev, and elliptic transfer functions of all orders.
This tutorial paper describes the methods for constructing fast algorithms for the computation of the discrete Fourier transform (DFT) of a real-valued series. The application of these ideas to all the major fast Four...
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This tutorial paper describes the methods for constructing fast algorithms for the computation of the discrete Fourier transform (DFT) of a real-valued series. The application of these ideas to all the major fast Fourier transform (FFT) algorithms is discussed, and the various algorithms are compared. We present a new implementation of the real-valued split-radix FFT, an algorithm that uses fewer operations than any other real-valued power-of-2-length FFT. We also compare the performance of inherently real-valued transform algorithms such as the fast Hartley transform (FHT) and the fast cosine transform (FCT) to real-valued FFT algorithms for the computation of power spectra and cyclic convolutions. Comparisons of these techniques reveal that the alternative techniques always require more additions than a method based on a real-valued FFT algorithm and result in computer code of equal or greater length and complexity.
The three‐dimensional Schr?dinger equationinverse scattering problem is solved using an orthogonalization approach. The plane waves propagating in free space are orthogonalized with respect to an inner product define...
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The three‐dimensional Schr?dinger equationinverse scattering problem is solved using an orthogonalization approach. The plane waves propagating in free space are orthogonalized with respect to an inner product defined in terms of a Jost operator. The resulting integral equation is identical to the generalized Gel’fand–Levitan equation of Newton, although the present derivation is simpler and more physical than that of Newton. Newton’s generalized Marchenko equation is derived from the defining integral equation for the Jost operator. These integral equations are shown to be solved by fast algorithms derived directly from the properties of their solutions. This paper thus presents a simple interpretation of Newton’s two integral equations, two fast algorithms for solving these integral equations, and relations between the various approaches. This is a generalization of previously obtained results, which are also reviewed here, for the one‐dimensional inverse scattering problem.
A new computationally efficient identification procedure is proposed for a non-Gaussian white noise driven linear, time-invariant, non-minimum phase system. The method is based on the idea of computing the complex cep...
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A new computationally efficient identification procedure is proposed for a non-Gaussian white noise driven linear, time-invariant, non-minimum phase system. The method is based on the idea of computing the complex cepstrum of higher-order cumulants of the system output. In particular, the differential cepstrum parameters of the system's impulse response are computed directly from higher-order cumulants via least-squares solution. The method is flexible enough to reconstruct the minimum and maximum phase components of the impulse response of MA, AR or ARMA systems without any prior knowledge of the type of the system. It does not require model order selection criteria and is shown to provide estimates with small bias and variance even with "short" length data records.
We consider multi-armed bandit problems with switching cost, and present asymptotically optimal adaptive allocation schemes. We illustrate an optimal allocation scheme for a large class of distributions which includes...
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We consider multi-armed bandit problems with switching cost, and present asymptotically optimal adaptive allocation schemes. We illustrate an optimal allocation scheme for a large class of distributions which includes members of the exponential family.
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