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A class of memristor circuits is obtained by cascading a static nonlinear two-port with a dynamical one-port. The terminals of the input port of the static nonlinearity represent the access nodes for each memristor in the class. The class may be splitted into two sub-classes, namely the current- and voltagecontrolled memristors. Two further sets of memristors may be identied within each of such sub-classes,...
Semi-supervised learning involves constructing predictive models with both labelled and unlabelled training data. The need for semi-supervised learning is driven by the fact that unlabelled data are often easy and cheap to obtain, whereas labelling data requires costly and time consuming human intervention and expertise. Semi-supervised methods commonly use self training, which involves using the...
Many interactive image processing approaches are based on semi-supervised learning, which employ both labeled and unlabeled data in its training process. In the interactive image segmentation problem, a human specialist labels some pixels of an object while the semi-supervised algorithm labels the remaining pixels of the segment. The particle competition and cooperation model is a recent graph-based...
In this paper, we train support vector regressors (SVRs) fusing sequential minimal optimization (SMO) and Newton's method. We use the SVR formulation that includes the absolute variables. A partial derivative of the absolute variable with respect to the associated variable is indefinite when the variable takes on zero. We determine the derivative value according to whether the optimal solution exits...
In this paper we propose a new statistical concept called directed generalized measure of association (dGMA) to quantify the amount of association transferred between subsystems in a system evolving in time. This paper is an improvement of the previously established method called generalized measure of association (GMA) by taking the conditional dependence between time-delay representation of subsystems...
This paper discusses performance of a winner-take-all neural network (WTANN) that is based on digital frequency-locked loops (DFLLs), especially its speed as well as its vector classification capability are studied. In the proposed WTANN input and weight vectors are conveyed by frequency-modulated signals, and neuron computation is carried out by the DFLL. Each DFLL uses a direct digital frequency...
We present an on-line method for concept change detection on labeled data streams. Our detection method uses a bivariate supervised criterion to determine if the data in two windows come from the same distribution. Our method has no assumption neither on data distribution nor on change type. It has the ability to detect changes of different kinds (mean, variance…). Experiments show that our method...
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