搜索结果: 1-15 共查到“数学 Signal”相关记录23条 . 查询时间(0.109 秒)
GENERALIZED SPARSE SIGNAL MIXING MODEL AND APPLICATION TO NOISY BLIND SOURCE SEPARATION
GENERALIZED SPARSE SIGNAL MIXING MODEL NOISY BLIND SOURCE SEPARATION
2015/9/29
Sparse constraints on signal decompositions are justified bytypical sensor data used in a variety of signal processing fields such as acoustics, medical imaging, or wireless, but moreover can lead to ...
Comparison of Wavelet and FFT Based Single Channel Speech Signal Noise Reduction Techniques
DWT DWPT wavelet wavelet packet FFT noise control speech enhancement noise cancellation filter
2015/9/29
This paper compares wavelet and short time Fourier transform based techniques for single channel speechsignal noise reduction. Despite success of wavelet denoising of images, it has not yet been widel...
Statistical Signal Processing for Novelty Detection
Support Vector Machines Health condition monitoring Novelty detection and Machine learning methods
2015/9/29
The goal of this article is to investigate and suggest techniques for health condition monitoring and diagnosis using machine learning from sensor data. In particular, this article overview and discus...
Fast Algorithms for Signal Reconstruction without Phase
Frames mutually unbiased bases equiangular frames projective 2-designs discrete chirps
2015/9/29
We derive fast algorithms for doing signal reconstruction without phase. This type of problem is important insignal processing, especially speech recognition technology, and has relevance for state to...
This paper presents a framework for discretetime signal reconstruction from absolute values of its shorttime Fourier coefficients. Our approach has two steps. In step one we reconstruct a band-diagona...
Extensions of No-Go Theorems to Many Signal Systems.
On signal reconstruction without phase
Frame Signal reconstruction Phase Speech recognition
2015/9/29
We will construct new classes of Parseval frames for a Hilbert space which allow signal reconstruction from theabsolute value of the frame coefficients. As a consequence, signal reconstruction can be ...
Maximum likelihood estimation of a nonparametric signal in white noise by optimal control
Nonparametric signal in white noise Maximum likelihood Smoothness classes Extremal problems Optimal control Iterative solution
2015/8/25
We study extremal problems related to nonparametric maximum likelihood estimation (MLE) of a signal in white noise.The aim is to reduce these to standard problems of optimal control which can be solve...
Optimal excitation signal design for frequency domain system identification using semidefinite programming
The optimal excitation signal and the dispersion function semidefinite programming linear matrix inequality (lmi)
2015/8/11
The paper discusses two methods of optimal excitation signal design for identification with Maximum Likelihood parameter estimation: The ‘classical’, dispersion function based method, and a new, semid...
Robust Uncertainty Principles: Exact Signal Reconstruction from Highly Incomplete Frequency Information
Random matrices free probability sparsity trigonometric expansions uncertainty principle convex optimization duality in optimization total-variation minimization image reconstruction linear programming
2015/6/17
This paper considers the model problem of reconstructing an object from incomplete frequency samples. Consider a discrete-time signal f ∈ CN and a randomly chosen set of frequencies Ω. Is it pos...
Stable Signal Recovery from Incomplete and Inaccurate Measurements
`1-minimization basis pursuit restricted orthonormality sparsity singular values of random matrices
2015/6/17
Suppose we wish to recover a vector x0 ∈ Rm (e.g. a digital signal or image) from incomplete and contaminated observations y = Ax0 + e; A is a n by m matrix with far fewer rows than columns (n m) an...
Estimating a Signal from a Magnitude Spectrogram via Convex Optimization
Estimating a Signal Magnitude Spectrogram Convex Optimization
2012/11/22
The problem of recovering a signal from the magnitude of its short-time Fourier transform (STFT) is a longstanding one in audio signal processing. Existing approaches rely on heuristics that often per...
Adaptive Sensing Performance Lower Bounds for Sparse Signal Estimation and Testing
adaptive sensing minimax lower bounds sequential experimental design sparsity-based models
2012/6/19
This paper gives a precise characterization of the fundamental limits of adaptive sensing for diverse estimation and testing problems concerning sparse signals. We consider in particular the setting i...
Efficient Information Aggregation Strategies for Distributed Control and Signal Processing
Efficient Information Aggregation Strategies Distributed Control Signal Processing
2010/12/14
This thesis will be concerned with distributed control and coordination of networks consisting of multiple, potentially mobile, agents. This is motivated mainly by the emergence of large scale network...
Noncoherent Interference Alignment: Trade Signal Power for Diversity Towards Multiplexing
Noncoherent Interference Alignment Trade Signal Power Diversity Multiplexing
2010/12/13
This paper proposes the first known universal interference alignment scheme for general (1 × 1)K interference networks, either Gaussian or deterministic, with only 2 symbol extension.