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A generalised Lasso iteratively reweighted scheme is here introduced to perform spatially regularised Hurst estimation on semi-local, weakly self-similar processes. This is extended further to the robust, heavy-tailed case whereupon the generalised M-Lasso is proposed. The design successfully incorporates both a spatial derivative in the generalised Lasso regulariser operator and a weight matrix formulated...
We design a smooth Lyapunov function for the Levant's Second Order Differentiator. The Lyapunov function construction method takes advantage of the structure of the system vector field to choose a candidate function. Both, the vector field and the candidate function belong to a special class of homogeneous functions. The problem of proving the positiveness of the function and the negativeness of its...
The automated detection of abandoned objects is a quickly developing and widely researched field in video processing with specific application to automated surveillance. In the recent years, a number of approaches have been proposed to automatically detect abandoned objects. However, these techniques require prior knowledge of certain properties of the object such as its shape and color, to classify...
This paper considers the detection of possible deviation from a nominal distribution for continuously valued random variables. Specifically, under the null hypothesis, samples are distributed approximately according to a nominal distribution. Any significant departure from this nominal distribution constitutes the alternative hypothesis. It is established that for such deviation detection where the...
A notion of fc-robustness for complex networks has received much attention recently. The motivation for this notion of robustness is to measure the effectiveness of local-information-based diffusion algorithms in the presence of adversarial nodes. In this paper, we first correct the relationship between fc-robustness and fc-connectivity studied in related work. Then we derive a sharp zero-one law...
Dishonest recommenders can have an impact upon the trust management framework of a mobile ad hoc network through the launch of an on-off attack pattern which involves periodic good behaviors so as to evade detection and avoid the trust degradation. The current paper presents the design of a recommendation trust update module which aims to achieve robustness against such on-off dishonest recommenders...
Steles are most important historical records of human civilizations, and most of them are collected by museums. Stele images are usually captured with flash compensation to the low-light condition of museum, resulting in annoying reflection spots due to the non-lambertian reflectance of polished stone steles. Observing that the reflection spots are bright at the center but fade away from the center,...
In this paper, we generalize Huber's criterion to multichannel sparse recovery problem of complex-valued measurements where the objective is to find good recovery of jointly sparse unknown signal vectors from the given multiple measurement vectors which are different linear combinations of the same known elementary vectors. This requires careful characterization of robust complex-valued loss functions...
‘Maximally Stable Extremal Regions’ (MSER) based interest points are frequently used for medical image registration on account of their robustness to noise, better localization, and good repeatability. However, if the objects in the image do not have sharp boundaries (as is the case with medical images), the number of MSER's detected is low. Also, MSER's are highly sensitive to image blur. This paper...
Existing methods for understanding the inner workings of convolutional neural networks have relied on visualizations, which do not describe the connections between the layers and units of the network. We introduce the prediction gradient as a measure of a neuron's relevance to prediction. Using this quantity, we study a relatively small convolutional neural network and make three observations. First,...
We aim to study the subspace structure of dataapproximately generated from multiple categories and removeerrors (e.g., noise, corruptions, and outliers) in the data aswell. Most previous methods for subspace analysis learn onlyone subspace, failing to discover the intrinsic complex structure, while state-of-the-art methods use data itself as the basis (self-expressiveness property), showing degraded...
Clustering high dimensional datasets is challenging due to the curse of dimensionality. One approach to address this challenge is to search for subspace clusters, i.e., clusters present in subsets of attributes. Recently the cartification algorithm was proposed to find such subspace clusters. The distinguishing feature of this algorithm is that it operates on a neighborhood database, in which for...
Identifying regions of interest (ROIs) in images is a very active research problem as it highly depends on the types and characteristics of images. In this paper we present a comparative evaluation of unsupervised learning methods, in particular clustering, to identify ROIs in solar images from the Solar Dynamics Observatory (SDO) mission. With the purpose of finding regions within the solar images...
Two "heterogeneous" information dissemination networks were established on the basis of sets of actual "rum or information" and "anti-rum or information" dissemination data involving a real micro logging event. Through empirical analysis of degree centrality, between ness centrality and closeness centrality, it was discovered that all three centrality indexes of the two...
Bio-medical research extends towards human voice and auditory systems day by day. Similarly it helps for the security issues. Emotion analysis and recognition for such purpose is a challenging task. To analyze and recognize, the emotions has been attempted in this piece of work. Initially, Sub-band spectral features have been extracted to characterize high arousal angry, happy, fear, surprise and...
A common assumption for Synthetic Aperture Radar (SAR) data, is that the intensity return from textureless areas follows a Gamma law with mean λ > 0 and L > 0 looks. Many image processing techniques need to estimate these parameters using small samples. Unfortunately, the presence of discrepant observations in SAR data occurs frequently, even when dealing with small samples. This is mostly caused...
A test-ecosystem is a configurable, modularized and scalable technology platform which combines test-relevant building blocks like roles, processes, strategies, methods, tools and technology from multiple sources and multiple vendors. Our objective is to provide an end-to-end testing environment for self-organizing and adaptive systems. Users customize test-ecosystem instances to suit needs dependent...
In this paper an attempt is made to design a dynamic state feedback based decoupler (PD compensator) for MIMO system. The condition for decoupling and mathematical expressions for the set of dynamic state feedback gain matrices (K, F and Γ) for a given decoupled system transfer function matrix is formulated. Further the robustness has been tested.
We present a robust particle filter based visual tracker based on an earlier approach called mean-transform which can track a window with orientation and scale changes. This work is the first work combining sparse coding, mean transform and particle filtering in visual tracking. We show that particle filter is effective in enhancing the mean-transform tracker. From the result, we see that such architecture...
Unmanned Aerial Vehicles (UAVs) is a kind of aircraft performing certain intelligence without pilot. To fulfill complex and practical tasks, accurate state estimation is an essential subject of UAVs. However, UAV is easy to be lost and hardly to be localized again in the unknown environments due to low features and strong flexibility in the previous SLAM system. In this paper, a rectification strategy...
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