Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 20 of 28 for “"statistical signal processing"”.
-
Topics in Robust Statistical Signal Processing
… addresses several problems in robust signal processing. The term "robust" in this context implies insensitivity to small deviations from the assumed statistical description of the signal and/or noise.
-
Difference-operator-based models in statistical signal processing
… of the continuous-time process. In this regime, statistical signal processing procedures derived from the difference-operator-based models tend to be better-conditioned than their conventional analogues, resulting in better numerical performance when implemented using finite-precision arithmetic. …
-
Continuous-time analog circuits for statistical signal processing
… high-speed, low-power, cost-effective, statistical signal processing. This methodology will have broad application to systems which can benefit from low-power, high-speed signal processing and offers the possibility of adaptable/programmable high-speed circuitry at frequencies where …
-
Statistical Signal Processing and Detector Optimization in Project 8
… mass scale. In this document, I investigate the statistically motivated limits to CRES signal detection and parameter estimation, as well as the resultant consequences on optimal detector configuration. I implement and test an application of the Viterbi algorithm for CRES signal reconstruction, …
-
A novel statistical signal processing approach for analysing high volatile expression profiles.
… of this research is to introduce new advanced statistical methods for analysing gene expression profiles to consequently enhance our understanding of the spatial gradients of the proteins produced by genes in a gene regulatory network (GRN). To that end, this research has three main …
-
A Bayesian framework for statistical signal processing and knowledge discovery in proteomic engineering
… Using the Bayesian framework in a statistical signal processing manner, mass spectrometry data is filtered and analyzed in order to estimate protein identity. This is done by a multi-stage process which compares probabilistic networks generated from mass spectrometry-based data with …
-
Machine Learning based Predictive Modeling of Stochastic Systems
Complex signals are ubiquitous in our daily lives, and interpreting and modeling them is vital for scientific advancement. Traditional methods for predictive modeling of complex signals include statistical signal processing and physics-based simulations. However, statistical signal processing …
-
A hierarchical wavelet-based framework for pattern analysis and synthesis
Despite their success in other areas of statistical signal processing, current wavelet-based image models are inadequate for modeling patterns in images, due to the presence of unknown transformations inherent in most pattern observations. In this thesis we introduce a hierarchical wavelet-based …
-
Generative models for neural time series with structured domain priors
… set out to research in the intersection of statistical signal processing and neuroscience (neural signal processing), my research advisor, Professor Emery N. Brown, explained at length that the signals from seemingly complex neural/biological systems are not purely random, but rather those …
-
Analogic for code estimation and detection
Analogic is a class of analog statistical signal processing circuits that dynamically solve an associated inference problem by locally propagating probabilities in a message-passing algorithm [29] [15]. In this thesis, we study an exemplary embodiment of analogic called Noise-Locked Loop(NLL) which …
-
Data selection in binary hypothesis testing
Traditionally, statistical signal processing algorithms are developed from probabilistic models for data. The design of the algorithms and their ultimate performance depend upon these assumed models. In certain situations, collecting or processing all available measurements may be inefficient or …
-
General Interference Suppression Technique For Diversity Wireless Rece
… etc. This research adopts space diversity and statistical signal processing for digital interference suppression in wireless receivers. The technique simplifies the analog front-end by eliminating the anti-aliasing filters and relaxing the requirements for IF bandpass filters and A/D …
-
Motion modeling and video processing
… by generalizing popular techniques in statistical signal processing--autoregressive (AR) models and moving average (MA) filtering. First, we show an equivalence between estimates from AR models (output of MA filtering) to the solution of a weighted least squares problem. This least …
-
Modeling and estimation in Gaussian graphical models : maximum-entropy methods and walk-sum analysis
Graphical models provide a powerful formalism for statistical signal processing. Due to their sophisticated modeling capabilities, they have found applications in a variety of fields such as computer vision, image processing, and distributed sensor networks. In this thesis we study two central …
-
Through-the-Wall Imaging and Multipath Exploitation
… behind reinforced concrete walls. The sensing signals reflected from the targets are significantly distorted and attenuated by the embedded metal bars. Using the surface formulation of the method of moments, we model the response of the reinforced walls, and incorporate their transmission …
-
Advanced classification of OFDM and MIMO signals with enhanced second order cyclostationarity detection
… to blindly distinguish OFDM from single carrier signals. We use the fourth order cumulants; an approach which in the past has been also applied to classify single carrier signals. A blind OFDM parameter estimation scheme was then followed, which includes the estimation of number of subcarriers, …
-
Stochastic Algorithms in Riemannian Manifolds and Adaptive Networks
… make a large impact in distributed control and signal processing applications. However, both literatures contain fundamental unsolved problems. The thesis is thus in two main parts. In part I, we consider stochastic differential equations (SDEs) evolving in a matrix Lie group. To undertake any …
-
Low-Complexity Iterative Receiver Design for Multi-Carrier Faster-Than-Nyquist Signaling Over Frequency-Selective Fading Channel
… Multi-carrier faster-than-Nyquist (MFTN) signaling reduces the symbol period satisfying the Nyquist criterion in the time domain and the minimum spacing of orthogonal subcarriers in the frequency domain for remarkably improving the spectral efficiency, which still occupies the same …
-
Robust Wireless Communications with Applications to Reconfigurable Intelligent Surfaces
… theory. Additionally, I perform robust statistical signal processing on the high-dimensional JSCC code showing significant noise immunity with drastic performance improvements at low signal-to-noise ratio (SNR) levels. The performance of the proposed JSCC codes is within 5 dB of the …
Page 1 of 2