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432
Advanced Spectral Methods for Climatic Time Series
, 2001
"... The analysis of uni or multivariate time series provides crucial information to describe, understand, and predict climatic variability. The discovery and implementation of a number of novel methods for extracting useful information from time series has recently revitalized this classical eld of ..."
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Cited by 220 (35 self)
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The analysis of uni or multivariate time series provides crucial information to describe, understand, and predict climatic variability. The discovery and implementation of a number of novel methods for extracting useful information from time series has recently revitalized this classical eld of study. Considerable progress has also been made in interpreting the information so obtained in terms of dynamical systems theory.
Perceptual Coding of Digital Audio
 Proceedings of the IEEE
, 2000
"... During the last decade, CDquality digital audio has essentially replaced analog audio. Emerging digital audio applications for network, wireless, and multimedia computing systems face a series of constraints such as reduced channel bandwidth, limited storage capacity, and low cost. These new applic ..."
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Cited by 156 (3 self)
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During the last decade, CDquality digital audio has essentially replaced analog audio. Emerging digital audio applications for network, wireless, and multimedia computing systems face a series of constraints such as reduced channel bandwidth, limited storage capacity, and low cost. These new applications have created a demand for highquality digital audio delivery at low bit rates. In response to this need, considerable research has been devoted to the development of algorithms for perceptually transparent coding of highfidelity (CDquality) digital audio. As a result, many algorithms have been proposed, and several have now become international and/or commercial product standards. This paper reviews algorithms for perceptually transparent coding of CDquality digital audio, including both research and standardization activities. The paper is organized as follows. First, psychoacoustic principles are described with the MPEG psychoacoustic signal analysis model 1 discussed in some detail. Next, filter bank design issues and algorithms are addressed, with a particular emphasis placed on the Modified Discrete Cosine Transform (MDCT), a perfect reconstruction (PR) cosinemodulated filter bank that has become of central importance in perceptual audio coding. Then, we review methodologies that achieve perceptually transparent coding of FM and CDquality audio signals, including algorithms that manipulate transform components, subband signal decompositions, sinusoidal signal components, and linear prediction (LP) parameters, as well as hybrid algorithms that make use of more than one signal model. These discussions concentrate on architectures and applications of
Analysis of dynamic brain imaging data
 Biophysical Journal
, 1999
"... ABSTRACT Modern imaging techniques for probing brain function, including functional magnetic resonance imaging, intrinsic and extrinsic contrast optical imaging, and magnetoencephalography, generate large data sets with complex content. In this paper we develop appropriate techniques for analysis an ..."
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Cited by 120 (4 self)
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ABSTRACT Modern imaging techniques for probing brain function, including functional magnetic resonance imaging, intrinsic and extrinsic contrast optical imaging, and magnetoencephalography, generate large data sets with complex content. In this paper we develop appropriate techniques for analysis and visualization of such imaging data to separate the signal from the noise and characterize the signal. The techniques developed fall into the general category of multivariate time series analysis, and in particular we extensively use the multitaper framework of spectral analysis. We develop specific protocols for the analysis of fMRI, optical imaging, and MEG data, and illustrate the techniques by applications to real data sets generated by these imaging modalities. In general, the analysis protocols involve two distinct stages: “noise ” characterization and suppression, and “signal ” characterization and visualization. An important general conclusion of our study is the utility of a frequencybased representation, with short, moving analysis windows to account for nonstationarity in the data. Of particular note are 1) the development of a decomposition technique (spacefrequency singular value decomposition) that is shown to be a useful means of characterizing the image data, and 2) the development of an algorithm, based on multitaper methods, for the removal of approximately periodic physiological artifacts arising from cardiac and respiratory sources.
A wavelet approach to wideband spectrum sensing for cognitive radios
 in Proc. 1st Int. Conf. on Cognitive Radio Oriented Wireless Networks & Coms. (CROWNCOM), Mykonos
, 2006
"... Abstract — In cognitive radio networks, the first cognitive task preceding any form of dynamic spectrum management is the sensing and identification of spectrum holes in wireless environments. This paper develops a wavelet approach to efficient spectrum sensing of wideband channels. The signal spect ..."
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Cited by 71 (2 self)
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Abstract — In cognitive radio networks, the first cognitive task preceding any form of dynamic spectrum management is the sensing and identification of spectrum holes in wireless environments. This paper develops a wavelet approach to efficient spectrum sensing of wideband channels. The signal spectrum over a wide frequency band is decomposed into elementary building blocks of subbands that are well characterized by local irregularities in frequency. As a powerful mathematical tool for analyzing singularities and edges, the wavelet transform is employed to detect and estimate the local spectral irregular structure, which carries important information on the frequency locations and power spectral densities of the subbands. Along this line, a couple of wideband spectrum sensing techniques are developed based on the local maxima of the wavelet transform modulus and the multiscale wavelet products. The proposed sensing techniques provide an effective radio sensing architecture to identify and locate spectrum holes in the signal spectrum. I.
A Tensor Framework for Multidimensional Signal Processing
 Linkoping University, Sweden
, 1994
"... ii About the cover The figure on the cover shows a visualization of a symmetric tensor in three dimensions, G = λ1ê1ê T 1 + λ2ê2ê T 2 + λ3ê3ê T 3 The object in the figure is the sum of a spear, a plate and a sphere. The spear describes the principal direction of the tensor λ1ê1ê T 1, where the lengt ..."
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Cited by 66 (8 self)
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ii About the cover The figure on the cover shows a visualization of a symmetric tensor in three dimensions, G = λ1ê1ê T 1 + λ2ê2ê T 2 + λ3ê3ê T 3 The object in the figure is the sum of a spear, a plate and a sphere. The spear describes the principal direction of the tensor λ1ê1ê T 1, where the length is proportional to the largest eigenvalue, λ1. The plate describes the plane spanned by the eigenvectors corresponding to the two largest eigenvalues, λ2(ê1ê T 1 + ê2ê T 2). The sphere, with a radius proportional to the smallest eigenvalue, shows how isotropic the tensor is, λ3(ê1ê T 1 + ê2ê T 2 + ê3ê T 3). The visualization is done using AVS [WWW94]. I am very grateful to Johan Wiklund for implementing the tensor viewer module used. This thesis deals with filtering of multidimensional signals. A large part of the thesis is devoted to a novel filtering method termed “Normalized convolution”. The method performs local expansion of a signal in a chosen filter basis which
R (2005) LFP power spectra in V1 cortex: the graded effect of stimulus contrast
 J Neurophysiol
"... First published February 9, 2005; doi:10.1152/jn.00919.2004. We recorded local field potentials (LFPs) and singleunit activity simultaneously in the macaque primary visual cortex (V1) and studied their responses to drifting sinusoidal gratings that were chosen to be “optimal ” for the single units. ..."
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Cited by 66 (1 self)
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First published February 9, 2005; doi:10.1152/jn.00919.2004. We recorded local field potentials (LFPs) and singleunit activity simultaneously in the macaque primary visual cortex (V1) and studied their responses to drifting sinusoidal gratings that were chosen to be “optimal ” for the single units. Over all stimulus conditions, the LFP spectra have much greater power in the lowfrequency band (�10 Hz) than higher frequencies and can be described as “1/f. ” Analysis of the total power limited to the low, gamma (25–90 Hz), or broad (8–240 Hz) frequency bands of the LFP as a function of stimulus contrast indicates that the LFP power gradually increases with stimulus strength across a wide band in a manner roughly comparable to the increase in the simultaneously recorded spike activity. However, the lowfrequency band power remains approximately constant across all stimulus contrasts. More specifically the gammaband LFP power increases differentially more with respect to baseline than either higher or lower bands as stimulus contrast increases. At the highest stimulus contrasts, we report as others have previously, that the power spectrum of the LFP typically contains an obvious peak in the gammafrequency band. The gammaband peak emerges from the overall broadband enhancement in LFP power at stimulus contrasts where most single units ’ responses have begun to saturate. The temporal/spectral structures of the LFP located in the gamma band— which become most evident at the highest contrasts—provide additional constraints on potential mechanisms underlying the stimulus response properties of spiking neurons in V1.
Sampling Properties of the Spectrum and Coherency of Sequences of Action Potentials
 Neural Computation
"... The spectrum and coherency are useful quantities for characterizing the temporal correlations and functional relations within and between point processes. This paper begins with a review of these quantities, their interpretation and how they may be estimated. A discussion of how to assess the statis ..."
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Cited by 52 (3 self)
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The spectrum and coherency are useful quantities for characterizing the temporal correlations and functional relations within and between point processes. This paper begins with a review of these quantities, their interpretation and how they may be estimated. A discussion of how to assess the statistical significance of features in these measures is included. In addition, new work is presented which builds on the framework established in the review section. This work investigates how the estimates and their error bars are modified by finite sample sizes. Finite sample corrections are derived based on a doubly stochastic inhomogeneous Poisson process model in which the rate functions are drawn from a low variance Gaussian process. It is found that, in contrast to continuous processes, the variance of the estimators cannot be reduced by smoothing beyond a scale which is set by the number of point events in the interval. Alternatively, the degrees of freedom of the estimators can be thought of as bounded from above by the expected number of point events in the interval. Further new work describing and illustrating a method for detecting the presence of a line in a point process spectrum is also presented, corresponding to the detection of a periodic modulation of the underlying rate. This work demonstrates that a known statistical test, applicable to continuous processes, applies, with little modification, to point process spectra, and is of utility in studying a point process driven by a continuous stimulus. While the material discussed is of general applicability to point processes attention will be confined to sequences of neuronal action potentials (spike trains) which were the motivation for this work. 1 Keywords and phrases: Spectrum, coherency, coherence, multitaper, lag window, spike train analysis, point processes, finite size effects in spectra, doubly stochastic Poisson process 1
Concurrent EEG/fMRI analysis by multiway Partial Least Squares
 NEUROIMAGE
, 2004
"... Data may now be recorded concurrently from EEG and functional ..."
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Cited by 50 (4 self)
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Data may now be recorded concurrently from EEG and functional