Spectral Analysis of Signals

By Usik Lee. 2009

2,890 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/8994dc7651f85fe6b20f3adca23fab2f73a70b9f

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Citations in the corpus

Multi-Pitch Estimation (2009, methodology): “, [22,29]), which relies on the design of a set of filters that pass power undistorted at specific frequen cies, here the harmonic frequencies, while minimizing the power at all other frequencies.”
On Parameter Identifiability of MIMO Radar (2007, methodology): “) circularly symmetric complex Gaussian random vectors with mean zero and unknown covariance , the CRB for can be obtained using the Slepian–Bangs formula [8].”
Estimating electromechanical modes and mode shapes using the multichannel ARMAX model (2013, methodology): “both off-line and on-line algorithms (see [16] and [20] for details).”
Sparse Methods for Direction-of-Arrival Estimation (2016, background): “According to [8, 9], the time delays at different sensors can be represented by simple phase shifts, resulting in the following data model:”
On Probing Signal Design For MIMO Radar (2006, background): “…is nondispersive, the base-band signal at the target location can be described by the expression (see, e.g., [9, Ch. 6 ]) (1) where is the carrier frequency of the radar, is the time needed by the signal emitted via the th transmit antenna to arrive at the target, denotes the conjugate…”
Fast communication: Fisher information matrix, Rao test, and Wald test for complex-valued signals and their applications (2014, methodology): “θ, then under the regularity condition the FIM can be written as [1–3]”
Robust Trend Inference with Series Variance Estimator and Testing-Optimal Smoothing Parameter (2011, background): “It belongs to the class of multi-window or multi-taper estimators (Thomson, 1982) and the class of lter-bank estimators (Stoica and Moses, 2005, ch. 5).”
Super-Resolution Power and Robustness of Compressive Sensing for Spectral Estimation With Application to Spaceborne Tomographic SAR (2012, background): “where λK is the Lagrange multiplier as a function of N and ε [22], [27].”
SPICE: A Sparse Covariance-Based Estimation Method for Array Processing (2011, methodology): “Under this reasonable assumption we can use the following non-parametric model for the output of the array (see, e.g. [1]) : where M is the total number of snapshots, N is the number of sensors in the array, y ( t ) ∈ C N × 1 is the t -th observed snapshot, a k ∈ C N × 1 denotes the array transfer…”
Direction-of-Arrival Estimation for Coprime Array via Virtual Array Interpolation (2018, methodology): “Furthermore, with the PSD constraint T (z) 0, if r = rank (T (z)) ≤ L − 1, the Hermitian Toeplitz matrix T (z) can be uniquely decomposed via Vandermonde decomposition as [39]”
MIMO Radar with Colocated Antennas (2007, methodology): “) circularly symmetric complex Gaussian random vectors with mean zero and unknown covariance Q, the CRB for {θk} can be obtained using the Slepian-Bangs formula [23].”
Parametric Rao Test for Multichannel Adaptive Signal Detection (2007, background): “…Gaussian distribution with mean vector ¹ and covariance matrix R, − denotes the Kronecker product, vec(¢) denotes the operation of stacking the columns of a matrix on top of each other, C denotes the complex number field, <f¢g takes the real part of the argument, and =f¢g takes the imaginary part.”
Jitter Buffer Compensation in Voice over IP Quality Estimation (2019, background): “For higher accuracy in delay prediction, sufficient number of samples from the signal is required [18], [19].”
Atomic Norm Denoising With Applications to Line Spectral Estimation (2012, background): “It is known that the autocorrelation matrix of a line spectral signal (see, for example Chapter 4 in [47]) can be written as a sum of a low rank matrix and if we assume that the phases are uniformly random.”
Fading Channel Prediction for Mobile Radio Adaptive Transmission Systems (2007, background): “Prediction Algorithms The theory of estimation, tracking, and prediction of random processes with slowly time-varying statistics is very well developed [1], [44]–[47].”