Computational Animal Theory: a Correlation-Detection Task
نویسندگان
چکیده
منابع مشابه
A Novel Fault Detection and Classification Approach in Transmission Lines Based on Statistical Patterns
Symmetrical nature of mean of electrical signals during normal operating conditions is used in the fault detection task for dependable, robust, and simple fault detector implementation is presented in this work. Every fourth cycle of the instantaneous current signal, the mean is computed and carried into the next cycle to discover nonlinearities in the signal. A fault detection task is complete...
متن کاملPerception, Action and Utility: The Tangled Skein
Normative theories of learning and decision-making are motivated by a computational-level analysis of the task facing an animal: what should the animal do to maximize future reward? However, much of the recent excitement in this field originates in how the animal arrives at its decisions and reward predictions—-algorithmic questions about which the computational-level analysis is silent. Answer...
متن کاملVlsi Implementation of an Efficient Template Matching Architecture Based on Feature Extraction
This paper presents a spectral architecture for template matching that combines edge detection, to find the similarity between input image and template. Generally template matching algorithms based on cross correlation suffers either from computational complexity or larger detection time. This architecture overcomes both problems and makes the system more reliable. Experiment results show the a...
متن کاملSystem-theoretic approach to image interest point detection
Interest point detection is a common task in various computer vision applications. Although a big variety of detector are developed so far computational efficiency of interest point based image analysis remains to be the problem. Current paper proposes a system–theoretic approach to interest point detection. Starting from the analysis of interdependency between detector and descriptor it is sho...
متن کاملFast Correlation Method for Partial Fourier and Hadamard Sensing Matrices in Matching Pursuit Algorithms
SUMMARY There have been many matching pursuit algorithms (MPAs) which handle the sparse signal recovery problem, called compressed sensing (CS). In the MPAs, the correlation step makes a dominant computational complexity. In this paper, we propose a new fast correlation method for the MPA when we use partial Fourier sensing matrices and partial Hadamard sensing matrices which are widely used as...
متن کامل