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319
The physics of optimal decision making: A formal analysis of models of performance in twoalternative forced choice tasks
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Deconvolution of impulse response in eventrelated BOLD fMRI
 NEUROIMAGE
, 1999
"... The temporal characteristics of the BOLD response in sensorimotor and auditory cortices were measured in subjects performing finger tapping while listening to metronome pacing tones. A repeated trial paradigm was used with stimulus durations of 167 ms to 16 s and intertrial times of 30 s. Both corti ..."
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Cited by 193 (2 self)
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The temporal characteristics of the BOLD response in sensorimotor and auditory cortices were measured in subjects performing finger tapping while listening to metronome pacing tones. A repeated trial paradigm was used with stimulus durations of 167 ms to 16 s and intertrial times of 30 s. Both cortical systems were found to be nonlinear in that the response to a long stimulus could not be predicted by convolving the 1s response with a rectangular function. In the shorttime regime, the amplitude of the response varied only slowly with stimulus duration. It was found that this character was predicted with a modification to Buxton’s balloon model. Wiener deconvolution was used to deblur the response to concatenated short episodes of finger tapping at different temporal separations and at rates from 1 to 4 Hz. While the measured response curves were distorted by overlap between the individual episodes, the deconvolved response at each rate was found to agree well with separate scans at each of the individual rates. Thus, although the impulse response cannot predict the response to fully overlapping stimuli, linear deconvolution is effective when the stimuli are separated by at least 4 s. The deconvolution filter must be measured for each subject using a shortstimulus paradigm. It is concluded that deconvolution may be effective in diminishing the hemodynamically imposed temporal blurring and may have potential applications in quantitating responses in eventrelated fMRI.
Spectral Processing of PointSampled Geometry
, 2001
"... We present a new framework for processing pointsampled objects using spectral methods. By establishing a concept of local frequencies on geometry, we introduce a versatile spectral representation that provides a rich repository of signal processing algorithms. Based on an adaptive tesselation of th ..."
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Cited by 98 (9 self)
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We present a new framework for processing pointsampled objects using spectral methods. By establishing a concept of local frequencies on geometry, we introduce a versatile spectral representation that provides a rich repository of signal processing algorithms. Based on an adaptive tesselation of the model surface into regularly resampled displacement fields, our method computes a set of windowed Fourier transforms creating a spectral decomposition of the model. Direct analysis and manipulation of the spectral coefficients supports effective filtering, resampling, power spectrum analysis and local error control. Our algorithms operate directly on points and normals, requiring no vertex connectivity information. They are computationally efficient, robust and amenable to hardware acceleration. We demonstrate the performance of our framework on a selection of example applications including noise removal, enhancement, restoration and subsampling.
Applying the harmonic plus noise model in concatenative speech synthesis
 IEEE Trans. Speech and Audio Processing
, 2001
"... Abstract—This paper describes the application of the harmonic plus noise model (HNM) for concatenative texttospeech (TTS) synthesis. In the context of HNM, speech signals are represented as a timevarying harmonic component plus a modulated noise component. The decomposition of a speech signal int ..."
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Cited by 93 (3 self)
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Abstract—This paper describes the application of the harmonic plus noise model (HNM) for concatenative texttospeech (TTS) synthesis. In the context of HNM, speech signals are represented as a timevarying harmonic component plus a modulated noise component. The decomposition of a speech signal into these two components allows for more naturalsounding modifications of the signal (e.g., by using different and better adapted schemes to modify each component). The parametric representation of speech using HNM provides a straightforward way of smoothing discontinuities of acoustic units around concatenation points. Formal listening tests have shown that HNM provides highquality speech synthesis while outperforming other models for synthesis (e.g., TDPSOLA) in intelligibility, naturalness, and pleasantness. Index Terms—Concatenative speech synthesis, fast amplitude, harmonic plus noise models, phase estimation, pitch estimation. I.
Efficient numerical methods in nonuniform sampling theory
, 1995
"... We present a new “second generation” reconstruction algorithm for irregular sampling, i.e. for the problem of recovering a bandlimited function from its nonuniformly sampled values. The efficient new method is a combination of the adaptive weights method which was developed by the two first named ..."
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Cited by 93 (10 self)
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We present a new “second generation” reconstruction algorithm for irregular sampling, i.e. for the problem of recovering a bandlimited function from its nonuniformly sampled values. The efficient new method is a combination of the adaptive weights method which was developed by the two first named authors and the method of conjugate gradients for the solution of positive definite linear systems. The choice of ”adaptive weights” can be seen as a simple but very efficient method of preconditioning. Further substantial acceleration is achieved by utilizing the Toeplitztype structure of the system matrix. This new algorithm can handle problems of much larger dimension and condition number than have been accessible so far. Furthermore, if some gaps between samples are large, then the algorithm can still be used as a very efficient extrapolation method across the gaps.
Selffocusing in the perturbed and unperturbed nonlinear Schrödinger equation in critical dimension
 SIAM J. APPL. MATH
, 1999
"... The formation of singularities of selffocusing solutions of the nonlinear Schrödinger equation (NLS) in critical dimension is characterized by a delicate balance between the focusing nonlinearity and diffraction (Laplacian), and is thus very sensitive to small perturbations. In this paper we introd ..."
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Cited by 61 (16 self)
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The formation of singularities of selffocusing solutions of the nonlinear Schrödinger equation (NLS) in critical dimension is characterized by a delicate balance between the focusing nonlinearity and diffraction (Laplacian), and is thus very sensitive to small perturbations. In this paper we introduce a systematic perturbation theory for analyzing the effect of additional small terms on self focusing, in which the perturbed critical NLS is reduced to a simpler system of modulation equations that do not depend on the spatial variables transverse to the beam axis. The modulation equations can be further simpli ed, depending on whether the perturbed NLS is power conserving or not. We review previous applications of modulation theory and present several new ones that include: Dispersive saturating nonlinearities, selffocusing with Debye relaxation, the Davey Stewartson equations, selffocusing in optical fiber arrays and the effect of randomness. An important and somewhat surprising result is that various small defocusing perturbations lead to a generic form of the modulation equations, whose solutions have slowly decaying focusingdefocusing oscillations. In the special case of the unperturbed critical NLS, modulation theory leads to a new adiabatic law for the rate of blowup which is accurate from the early stages of selffocusing and remains valid up to the singularity point. This adiabatic law preserves the lens transformation property of critical NLS and it leads to an analytic formula for the location of the singularity as a function of the initial pulse power, radial distribution and focusing angle. The asymptotic limit of this law agrees with the known loglog blowup behavior. However, the loglog behavior is reached only after huge amplifications of the initial amplitude, at which point the physical
Orthogonal transmultiplexers in communication: A review
 IEEE Trans. on Signal Processing
, 1998
"... Abstract — This paper presents conventional and emerging applications of orthogonal synthesis/analysis transform configurations (transmultiplexer) in communications. It emphasizes that orthogonality is the underlying concept in the design of many communication systems. It is shown that orthogonal fi ..."
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Cited by 53 (8 self)
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Abstract — This paper presents conventional and emerging applications of orthogonal synthesis/analysis transform configurations (transmultiplexer) in communications. It emphasizes that orthogonality is the underlying concept in the design of many communication systems. It is shown that orthogonal filter banks (subband transforms) with proper time–frequency features can play a more important role in the design of new systems. The general concepts of filter bank theory are tied together with the applicationspecific requirements of several different communication systems. Therefore, this paper is an attempt to increase the visibility of emerging communication applications of orthogonal filter banks and to generate more research activity in the signal processing community on these topics. I.
Recursive Gaussian Derivative Filters
, 1998
"... We propose a new strategy to design recursive implementations of the Gaussian filter and Gaussian regularized derivative filters. Each recursive filter consists of a cascade of two stable N order subsystems (causal and anticausal). The computational complexity is 2N multiplications per pixel per d ..."
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Cited by 49 (2 self)
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We propose a new strategy to design recursive implementations of the Gaussian filter and Gaussian regularized derivative filters. Each recursive filter consists of a cascade of two stable N order subsystems (causal and anticausal). The computational complexity is 2N multiplications per pixel per dimension independent of the size (s) of the Gaussian kernel. The filter coefficients have a closedform solution as a function of scale (s) and recursion order N (N=3,4,5). The recursive filters yield a high accuracy and excellent isotropy in nD space.
The Chirplet Transform: Physical Considerations
, 1995
"... We consider a multidimensional parameter space formed by inner products of a parameterizable family of chirp functions with a signal under analysis. We propose the use of quadratic chirp functions (which we will call qchirps for short), giving rise to a parameter space that includes both the timef ..."
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Cited by 49 (3 self)
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We consider a multidimensional parameter space formed by inner products of a parameterizable family of chirp functions with a signal under analysis. We propose the use of quadratic chirp functions (which we will call qchirps for short), giving rise to a parameter space that includes both the timefrequency plane and the timescale plane as twodimensional subspaces. The parameter space contains a "timefrequencyscale volume ", and thus encompasses both the shorttime Fourier transform (as a slice along the time and frequency axes), and the wavelet transform (as a slice along the time and scale axes). In addition to time, frequency, and scale, there are two other coordinate axes within this transform space: shearintime (obtained through convolution with a qchirp) and shearin frequency (obtained through multiplication by a qchirp). Signals in this multidimensional space can be obtained by a new transform which we call the "qchirplet transform", or simply the "chiplet transform". ...