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In this paper, we propose an adaptive framework for the variable step size of the fractional least mean square (FLMS) algorithm. The proposed algorithm named the robust variable step size-FLMS (RVSS-FLMS), dynamically updates the step size of the FLMS to achieve high convergence rate with low steady state error. For the evaluation purpose, the problem of system identification is considered. The experiments...
A function that outputs a feature vector from the perceptual contents of the input video is called a perceptual video hashing function and the output feature vector that characterizes the perceptual contents of the input video is called the perceptual video hash. This hash must be robust to the manipulations that preserves the perceptual contents of the video and fragile to the modifications that...
The purpose of this paper is to derive new asymptotic properties of the robust adaptive normalized matched filter (ANMF). More precisely, the ANMF built with Tyler estimator (TyE-ANMF) is analyzed under the framework of complex elliptically symmetric (CES) distributions. We show that the distribution of TyE-ANMF can be accurately approximated by the well-known distribution of the ANMF built with the...
The digital image watermarking technology is widely used to protect intellectual property and to authenticate digital contents in the network environment. The aim of the paper is to invoke the improved Laplacian Pyramid transform to develop a new image watermarking scheme. Specifically, the host image is decomposed and reconstructed by using the improved Laplacian Pyramid transform. Then, the mid...
Source apportionment is usually tackled with blind Positive/Non-negative Matrix factorization (PMF/NMF) methods. However, the obtained results may be poor due to the dependence between some rows of the second factor. We recently proposed to inform the estimation of this factor using some prior knowledge provided by chemists—some entries are set to some fixed values—and the sum-to-one property of each...
Reliable characterization of different signals is essential for better understanding of their generating and propagation phenomena. Many works in this area have been based on detecting special patterns or clusters in data, and event detection using parametric models. In this paper we present an approach making use of the short-term time-frequency Renyi entropy and an algorithm to discriminate between...
Activity recognition and activity boundary detection are two separate long-standing challenges in the image processing literature. In activity recognition, a predefined set of activities is classified using features. Often, subjects do not perform meaningful activities in all the frames, thus requiring the identification of the beginning and the end of the set of contiguous frames containing the activity...
Joint detection and estimation is an important yet little-studied problem that arises in many signal processing applications. In this paper, a sequential and robust solution approach is presented. To design the test fulfilling constraints on the error probabilities and the quality of the estimate, the problem is converted into an unconstrained form and subsequently solved using Linear Programming...
The adaptive Lasso (Least Absolute Shrinkage and Selection Operator) obtains oracle variable selection property by using cleverly chosen adaptive weights for regression coefficients in the ℓ1-penalty. In this paper, in the spirit of M-estimation of regression, we propose a class of adaptive M-Lasso estimates of regression and scale as solutions to generalized zero subgradient equations. The defining...
Many signal and image processing applications, including texture analysis, radar detection or EEG signal classification, require the computation of a centroid from a set of covariance matrices. The most popular approach consists in considering the center of mass. While efficient, this estimator is not robust to outliers arising from the inherent variability of the data or from faulty measurements...
Sophisticated cyber security threats, such as advanced persistent threats, rely on infecting end points within a targeted security domain and embedding malware. Typically, such malware periodically reaches out to the command and control infrastructures controlled by adversaries. Such callback behavior, called beaconing, is challenging to detect as (a) detection requires long-term temporal analysis...
With the development of the Internet, authentication and copyright protection of digital products becomes an important issue. In this paper, a zero-watermarking algorithm based on audio content is proposed, which can stand against synchronization attacks. The audio signal is divided into several segments according to the size of watermarking image. After that, SVD transform is performed for each matrix...
Image matching and object extraction have been at the heart of computer vision research since the last two decades invigorated by the introduction of SIFT features by David Lowe. This paper proposes an approach for the same for its application to a specific problem, i.e. to extract the rectangular pantograph region from the cheque images used by banks in India. The proposed approach relies upon maximally...
A novel method of semi-blind image watermarking is proposed in this paper. The proposed method is performed by using slant transform along with lifting wavelet transform and singular value decomposition. Host images are decomposed using Lifting wavelet transform. Singular value decomposition is applied on its selected sub band. Singular value decomposed cover image is watermarked using slant transformed...
Automatic speech recognition (ASR) has been extensively studied during the past few decades. Most of present systems are based on statistical modeling, both at the acoustic and linguistic levels, not only for recognition, but also for understanding. Speech recognition in adverse conditions has recently received increased attention since noise resistance has become one of the major bottlenecks for...
Non-invasive respiration monitoring of a person has many human-centric applications. In this paper, we use received signal strength indicator (RSSI) from a wireless network to perform non-contact respiration rate monitoring. We develop a low-cost monitoring system that uses multiple commercial-off-the-shelf (COTS) radios operating on multiple frequency channels. We propose a maximum likelihood estimator...
A digital signal processing approach to estimate and reject disturbances under an active disturbance rejection control (ADRC) methodology is presented. In this paper a technique to assess the current values of the disturbance based on the previous input and output signals is developed. The on-line disturbance estimation is made through the use of a polynomial least squares regression. An excess in...
A novel signal processing method based on custom-made Wavelet Transform (WT) is presented for robust detection of fringes contained in the interferometric signal of Self-Mixing (SM) laser diode sensors. It enables the measurement of arbitrarily-shaped vibrations even in the corruptive presence of speckle. Our algorithm is based on the pattern recognition capability of the customized WT for identifying...
Progress in signal processing continues to enable welcome advances in high-frequency (HF) radio performance and efficiency. The latest data waveforms use channels wider than 3 kHz to boost data throughput and robustness. This has driven the need for a more capable Automatic Link Establishment (ALE) system that links faster and adapts the wideband HF (WBHF) waveform to efficiently use available spectrum...
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