Demosaicking with compressive sensing

Sparse signals can be recovered with less number of measurements compared to standard methods using Compressive Sensing (CS) theory. In digital cameras, color filter arrays (CFA) are used to sample each color band with less measurements than the normal. The color images are reconstructed using interpolation of measured pixel values. In this study, assuming images are sparse or compressible in a basis demosaicking is done with CS using the measurements from the CFA pattern. Separate, together and joint sparsity models are used for reconstructing images. Reconstructed sparsity levels for used CFA patterns are found. The images reconstructed with the proposed method are compared with the results from bilinear interpolation. © 2012 IEEE

Distinguishing Electronic Devices Using Harmonic Radar

IEEE Radar Conference (RadarConf) (2017 : The Westin SeattleSeattle; United States)A new approach to distinguishing electronic circuits using nonlinear/harmonic radar is presented in this paper. The radar transmits a single tone signal to the electronic circuits, consisting of nonlinear components, and exploits received harmonic response for separation. Unlike previous studies, the transmitted signal power is swept within a determined range so that the received powers at each harmonic are analyzed to capture the nonlinear characteristics. To predict the behavior of the nonlinear circuits such as diode clamper, diode limiter and full wave rectifier, certain statistical features of the received powers are analyzed. We show that the received power at the harmonics are distinctive for each circuit using Euclidean distances of features in feature space

Distinguishing Electronic Devices Using Harmonic Radar Based on a Linear Model

21st International Conference on Electromagnetics in Advanced Applications, ICEAA (2019 ; Granada, Spain)A linear model using harmonic radar to distinguish electronic devices is proposed in this article. Nonlinear characteristics of the electronic devices are captured by using power varying signals as incident waves. Three harmonics of the received powers are analyzed in harmonic space. As a major contribution of this study, power series model is employed to calculate the input-output relationship of the electronic devices. As a first in this area, we construct a linear model that relates the measurements to the vectors of parameters characterizing the nonlinear behaviors of the Electronic Circuits Under Test (ECUT). Each nonlinear circuit has a distinct response to a single-tone time-varying signal with varying power. Subsequently, a unique unknown deterministic vector of parameters can be estimated from this linear model for each device. We estimate the unique vectors of parameters using a Maximum Likelihood Estimator (MLE) in the presence of Complex White Gaussian Noise (CWGN). We show that the statistical features of the normalized estimated vectors of parameters can be used to distinguish various nonlinear electronic devices

Classification of Electronic Devices Using a Frequency-Swept Harmonic Radar Approach

A new method to classify electronic devices using a Frequency-Swept Harmonic Radar (FSHR) approach is proposed in this paper. The FSHR approach enables us to utilize the frequency diversity of the harmonic responses of the electronic circuits. Unlike previous studies, a frequency-swept signal with a constant power is transmitted to Electronic Circuits Under Test (ECUTs). The harmonic response to a frequency-swept transmitted signal is found to be distinguishable for different types of ECUTs. Statistical and Fourier features of the harmonic responses are derived for classification. Later, the harmonic characteristics of the ECUTs are depicted in 3D harmonic and feature spaces for classification. Three-dimensional harmonic and feature spaces are composed of the first three harmonics of the re-radiated signal and the statistical or Fourier features, respectively. We extensively evaluate the performance of our novel method through Monte Carlo simulations in the presence of noise.</jats:p

Classification of Electronic Devices Using a Frequency-Swept Harmonic Radar Approach

A new method to classify electronic devices using a Frequency-Swept Harmonic Radar (FSHR) approach is proposed in this paper. The FSHR approach enables us to utilize the frequency diversity of the harmonic responses of the electronic circuits. Unlike previous studies, a frequency-swept signal with a constant power is transmitted to Electronic Circuits Under Test (ECUTs). The harmonic response to a frequency-swept transmitted signal is found to be distinguishable for different types of ECUTs. Statistical and Fourier features of the harmonic responses are derived for classification. Later, the harmonic characteristics of the ECUTs are depicted in 3D harmonic and feature spaces for classification. Three-dimensional harmonic and feature spaces are composed of the first three harmonics of the re-radiated signal and the statistical or Fourier features, respectively. We extensively evaluate the performance of our novel method through Monte Carlo simulations in the presence of noise