Browsing George R. Brown School of Engineering by Title
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Nonlinear Fault Detection for Hydraulic Systems
(20030101)One of the most important areas in the robotics industry is the development of robots capable of working in hazardous environments. As humans cannot safely or cheaply work in these environments, providing a high level ... 
Nonlinear Fault Detection for Hydraulics: Recent Advances in Fault Diagnosis and Fault Tolerance for Mechatronic Systems
(20021001)One of the most important areas in the robotics industry is the development of robots capable of working in hazardous environments. As humans cannot safely or cheaply work in these environments, providing a high level ... 
Nonlinear neural codes
(20151203)Most natural taskrelevant variables are encoded in the early sensory cortex in a form that can only be decoded nonlinearly. Yet despite being a core function of the brain, nonlinear population codes are rarely studied and ... 
Nonlinear phase FIR filter design with minimum LS error and additional constraints
(19940701)We examine the problem of approximating a complex frequency response by a realvalued FIR filter according to the <i>L<sub>2</sub></i> norm subject to additional inequality constraints for the complex error function. ... 
Nonlinear Processing of a Shift Invariant DWT for Noise Reduction
(19950320)A novel approach for noise reduction is presented. Similar to Donoho, we employ thresholding in some wavelet transform domain but use a nondecimated and consequently redundant wavelet transform instead of the usual orthogonal ... 
Nonlinear Processing of a Shift Invariant DWT for Noise Reduction
(19950420)A novel approach for noise reduction is presented. Similar to Donoho, we employ thresholding in some wavelet transform domain but use a nondecimated and consequently redundant wavelet transform instead of the usual orthogonal ... 
Nonlinear Signal Models: Geometry, Algorithms, and Analysis
(20130724)Traditional signal processing systems, based on linear modeling principles, face a stifling pressure to meet presentday demands caused by the deluge of data generated, transmitted and processed across the globe. Fortunately, ... 
Nonlinear System Identification Based on a Fock Space Framework
(19790520)A method is presented for the identification of a nonlinear system represented by an operator V:E>Y, where the input space E is a separable Hilbert space over the field of complex numbers and the output space Y is the ... 
Nonlinear Wavelet Processing for Enhancement of Images
(19940520)In this note we apply some recent results on nonlinear wavelet analysis to image processing. In particular we illustrate how the (soft) thresholding algorithm due to Donoho and Johnstone can successfully be used to remove ... 
Nonlinear Wavelet Transforms for Image Coding
(19971101)We examine the central issues of invertibility, stability, artifacts, and frequencydomain characteristics in the construction of nonlinear analogs of the wavelet transform. The lifting framework for wavelet construction ... 
Nonlinear Wavelet Transforms for Image Coding via Lifting
(20031201)We investigate central issues such as invertibility, stability, synchronization, and frequency characteristics for nonlinear wavelet transforms built using the lifting framework. The nonlinearity comes from adaptively ... 
Nonlinear WignerVille Spectrum Estimation using Wavelet Soft Thresholding
(19950401)The large variance of the WignerVille distribution makes smoothing essential for producing readable estimates of the timevarying power spectrum of noise corrupted signals. Since linear smoothing trades reduced variance ... 
NonlinearPhase MaximallyFlat FIR Filter Deisgn
(19960920)This paper reports a new analytic technique for the design of nonlinearphase maximallyflat lowpass FIR filters. By subjecting the response magnitude and the group delay (individually) to differing numbers of flatness ... 
Nonparametric prediction of mixing time series
(1992)Prediction of future timeseries values, based on a finite set of available observations, is a prevalent problem in many branches of science and engineering. By making the assumption that the time series is either Gaussian ... 
Nonparametric, Low Bias, and Low Variance TimeFrequency Analysis of Myoelectric Signals
(19950901)The authors apply Thomson's multiple window method (see D. Thomson â Spectrum Estimation and Harmonic Analysisâ , Proc. of the IEEE, vol. 70, no. 9, p. 105596) to myoelectric signal timefrequency analysis for the first ... 
Nonresonant surface enhanced Raman optical activity
(2009)Nanoshells (NS) and nanoparticles (NP) are tunable plasmonic particles that can be precisely engineered for specific applications including surface enhanced spectroscopies. A new, general method for the synthesis of ... 
Nonstationary signal classification using pseudo power signatures
(19980620)This paper deals with the problem of classification of nonstationary signals using signatures which are essentially independent of the signal length. We develop the notion of a separable approximation to the Continuous ... 
Nonstationary signal classification using pseudo power signatures: The Matrix SVD Approach
(19991220)This paper deals with the problem of classification of nonstationary signals using signatures which are essentially independent of the signal length. This independence is a requirement in common classification problems ... 
Nonstationary Signal Enhancement Using The Wavelet Transform
(19960320)Conventional signal processing typically involves frequency selective techniques which are highly inadequate for nonstationary signals. In this paper, we present an approach to perform timefrequency selective processing ...