Artificial Neural Network Approach to the Analytic Continuation Problem
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In this paper we present analog current mode Euclidean distance calculation (EDC) block, which calculates the distance between two current vectors. The proposed circuit is an important part of the CMOS-implemented Kohonen’s neural network (KNN) designed fo ...
Morphology plays an important role in the computational properties of neural systems, affecting both their functionality and the way in which this functionality is developed during life. In computer-based models of neural networks, artificial evolution is ...
Perceptual learning is the ability to modify perception through practice. As a form of brain plasticity, perceptual learning has been studied for more than thirty years in different fields including psychology, neurophysiology and computational neuroscienc ...
Over the last decades, calibration techniques have been widely used in robotics since they represent a cost-effective solution for improving the accuracy of robots and machine-tools. They only involve software modification without the necessity of revising ...
The evolution of artificial neural networks (ANNs) is often used to tackle difficult control problems. There are different approaches to the encoding of neural networks in artificial genomes. Analog Genetic Encoding (AGE) is a new implicit method derived f ...
A two-level procedure designed for the estimation of constitutive model parameters is presented in this paper. The neural network (NN) approach at the first level is applied to achieve the first approximation of parameters. This technique is used to avoid ...
memory in biological neural networks. Similarly, artificial neural networks could benefit from modulatory dynamics when facing certain types of learning problem. Here we test this hypothesis by introducing modulatory neurons to enhance or dampen neural pla ...
Motivated by biological neural networks and distributed sensing networks, we study how pooling networks – or quantizers – with random thresholds can be used in detection tasks. We provide a brief overview of the use of deterministic quantizers in detection ...
In this paper we propose a method for classifying regions of images and videos frames into text and non-text regions using support vector machine (SVM). Different features are proposed to characterise the texture formed by text characters and background. S ...
This is the second episode of the Bayesian saga started with the tutorial on the Bayesian probability. Its aim is showing in very informal terms how supervised learning can be interpreted from the Bayesian viewpoint. The focus is put on supervised learning ...