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Instantaneous frequency estimation of signals in a high noise environment is analyzed in the paper. An algorithm based on Ant colony optimization and Wigner distribution is proposed for solving the considered estimation problem. The proposed approach has been applied and tested on mono-component frequency-modulated signals. Numerical examples are given in order to demonstrate the algorithm's performances...
Among the many parameters of human life, which are subject to intensive monitoring, one can specify the frequency of of respiratory action. The measurement of such physical quantity can be performed directly by tracking the activity of the respiratory organs, as well as indirectly through the breathing frequency estimation based on the ECG signal. This paper presents a method to assess the respiratory...
The paper presents a method for estimating the shaft position of a synchronous motor with permanent magnets (PMSM) for the zero and very low speed range. The method is based on the analysis of the high frequency currents, which are induced by the additional test voltage in a stationary coordinate system associated with the stator. Although this method involves the identification of currents hodograph,...
We study optimal estimation for sparse principal component analysis when the number of non-zero elements is small but on the same order as the dimension of the data. We employ approximate message passing (AMP) algorithm and its state evolution to analyze what is the information theoretically minimal mean-squared error and the one achieved by AMP in the limit of large sizes. For a special case of rank...
We study the excess mean square error (EMSE) above the minimum mean square error (MMSE) in large linear systems where the posterior mean estimator (PME) is evaluated with a postulated prior that differs from the true prior of the input signal. We focus on large linear systems where the measurements are acquired via an independent and identically distributed random matrix, and are corrupted by additive...
In this paper, a new spectrum sensing framework is proposed for radar communications, which recovers other informative states associated with realistic radar environments, e.g. fading channel gains and unknown noise variance, when detecting the occupancy of primary-band. We firstly formulate a dynamic state-space model by full considering the unknown noise variance and time-variant flat fading channel...
Hydraulic systems are one of the most common power source in both transport systems (i.e. aircrafts) and industrial systems. Electro hydraulic servovalves are critical components and often subjected to failures. This article presents a method to estimate degradation in a servovalve using an application of the Fading Extended Kalman Filter for system identification. A single failure mode related to...
We consider change-point estimation in a sequence of high-dimensional signals given noisy observations. Classical approaches to this problem such as the filtered derivative method are useful for sequences of scalar-valued signals, but they have undesirable scaling behavior in the high-dimensional setting. However, many high-dimensional signals encountered in practice frequently possess latent low-dimensional...
The modeling of interconnections is very much important, as the performance of VLSI circuit is limited by interconnect related failure modes, such as coupled noise and delay. Inductance along with capacitance causes noise in the signals, which may adversely affect the performance of the circuit and signal integrity. An analytical expression for crosstalk noise voltage is derived in this study using...
Recent years have shown increases in virtual 3D perception and applications, many of these applications require 3D model reconstruction from high quality LIDAR scans. High quality 3D models may be acquired from a collection of overlapping LIDAR scans which need to be registered or aligned to a common coordinate system. This paper investigates the use of a novel implementation of trilateration for...
We consider the problem of spatiotemporal sampling in an evolutionary process xn = Anx where an unknown operator A driving an unknown initial state x is to be recovered from a combined set of coarse spatial samples {χ|Ωο, x(1)|Ωι,· · ·, x(N)|ΩN}. In this paper, we will study the case of infinite dimensional spatially invariant evolutionary process, where the unknown initial signals x are modeled as...
Parameter estimation for exponential sums is a classical problem in signal processing. Recently, a new concept for estimating parameters of bivariate exponential sums has been proposed. The resulting method relies on parameter estimations for univariate exponential sums along several lines in the plane. These (univariate) parameter estimations are being used to first compute the projections of the...
Discrete-time estimation of rigid body attitude and angular velocity without any knowledge of the attitude dynamics model, is treated using the discrete Lagrange-d'Alembert principle. Using body-fixed sensor measurements of direction vectors and angular velocity, a Lagrangian is obtained as the difference between a kinetic energy-like term that is quadratic in the angular velocity estimation error,...
This paper utilizes system observability to guide monocular SLAM. Instead of providing all measured features then performing data-driven outlier rejection (such as with RANSAC), we propose to identify only the minimal subset of features which form an optimally observable SLAM subsystem for localization. Modeling the SLAM system as a discrete time system with piece-wise linear SE〈3〉 motion, complete...
The orientation field of a fingerprint is crucial for feature extraction and matching. However, estimation of orientation fields in latents is very challenging because latents are usually of poor quality. Inspired by the superiority of convolutional neural networks (ConvNets) for various classification and recognition tasks, we pose latent orientation field estimation in a latent patch to a classification...
Estimating the ground plane is often one of the first steps in geometric reasoning processes as it offers easily accessible context knowledge. Especially unconstrained platforms that capture video from egocentric viewpoints can benefit from such knowledge in various ways. A key requirement here is keeping orientation, which can be greatly achieved by keeping track of the ground. We present an approach...
Clock jitter is a crucial factor in high speed and high performance Analog-to-Digital Converter (ADC) testing. Random clock jitter increases the noise floor in the ADC output spectrum making it difficult to obtain the true ADC Signal to Noise Ratio (SNR). Periodic Jitter generates spurs in the ADC output spectrum. Another well-known challenge is to achieve precise coherent sampling. This paper proposes...
This paper presents a novel method to solve the estimation of the amplitudes and phases of different harmonic components contained in a power electrical signal, based on Particle Swarm Optimizer with Natural Selection (PSONS). PSONS is an Evolutionary Algorithm (EA) with the natural selection mechanism. The proposed method utilizes PSONS to estimate the phases of the harmonics and a standard least-square...
Reliable surface normal computation is fundamental for a broad range of computer vision application areas, e.g. object segmentation, classification and recognition. Naturally, the surface normal is computed on the acquired depth data, whereby the normal quality is dependent on noise performance and resolution of the underlying image modality. The tendency of combining different imaging sensors into...
The paper describes algorithms of the nonparametric power estimation by summation of the products of the amplitude discrete Fourier transform (DFT) coefficients when simultaneously of sampling is assumed. As with energy-based approach for the amplitude square estimation of the one-channel signal, the apparent power in the two-channel case can be estimated with the multiplied amplitude DFT coefficients...
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