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sensor
sensor

... (some micro volts). ...
Sensors in the field of Sleep
Sensors in the field of Sleep

... voltages (some micro volts). ...
A Computational Model of Human Planning in the Traveling Salesman...  Simone Cutini () Andrea Di Ferdinando ()
A Computational Model of Human Planning in the Traveling Salesman... Simone Cutini () Andrea Di Ferdinando ()

... dynamics for the choice of the heuristic; 3) a motor map, based on population codes, that executes the pathway at the spatial level. Moreover, the presence of saliency maps, recurrent connections and inhibitory mechanisms allow us to simulate the incremental aspect of visuo-spatial planning and the ...
IOSR Journal of Electronics and Communication Engineering (IOSR-JECE)
IOSR Journal of Electronics and Communication Engineering (IOSR-JECE)

... sub-divided into normal sample and abnormal sample. These two samples are given to the mapping functions. In the testing part, the isolated points were identified and the testing images was then assessed by using the new method. Here the SVM classifier is used. This classifier is used to analyze dat ...
WAIC AND WBIC ARE INFORMATION CRITERIA FOR SINGULAR
WAIC AND WBIC ARE INFORMATION CRITERIA FOR SINGULAR

... A statistical model is said to be regular if the map taking parameters to probability distributions is one-to-one and if Fisher information matrix is always positive definite. If otherwise it is called singular. Many statistical models and learning machines which have hierarchical structures, hidden ...
View PDF - CiteSeerX
View PDF - CiteSeerX

... legend to Fig. 1 for description of the peak-interval procedure). As can be seen from Figure 1, interval-timing behavior has some characteristic properties that are consistent between these (and other) species, which is the first criterion for postulating the existence of a common interval timing me ...
Neuron Stations
Neuron Stations

to get the file
to get the file

... 5) Calculating with Neurons I: adding, subtracting, multiplying, dividing 5,6) Calculating with Neurons II: Integration, differentiation 6) Calculating with Neurons III: networks, vector-/matrix- calculus, assoc. memory 6,7) Information processing in the cortex I: Neurons as filters 7) Information p ...
On the computational architecture of the neocortex
On the computational architecture of the neocortex

Biological Bases of Behavior, Barron`s Neuroanatomy, pages 78
Biological Bases of Behavior, Barron`s Neuroanatomy, pages 78

Lecture Notes in Artificial Intelligence 4911
Lecture Notes in Artificial Intelligence 4911

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preprint

Artificial Neural Networks
Artificial Neural Networks

Neural, Fuzzy Expert Systems
Neural, Fuzzy Expert Systems

Hydrological Neural Modeling aided by Support Vector Machines
Hydrological Neural Modeling aided by Support Vector Machines

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Modelling the Development of Mirror Neurons for Auditory
Modelling the Development of Mirror Neurons for Auditory

Assumptions of Decision-Making Models in AGI
Assumptions of Decision-Making Models in AGI

... measured by a (utility or reward) value function defined on states, and the best action is the one that with the maximum expectation. The assumption on budget: The system can afford the computational resources demanded by the selection algorithm. There are many situations where the above assumptions ...
PDF file
PDF file

A Novel Approach for Constructing Conversational Agents using
A Novel Approach for Constructing Conversational Agents using

... including: CAs as advanced help assistants associated with a specific learning environment or tool. CAs as personal coaches equipped with specific domain knowledge and CAs as role-playing actors in simulated experiential learning environments. Roda et al. [7] applied CAs to operate in domains such a ...
The Nervous System
The Nervous System

... Characteristics of Neurons 1) Neurons can be stimulated: they react to chemical signals by transforming them into electrical signals. 2) Neurons are conductive: they transmit nerve impulses to other cells. 3) Neurons are needy: they require great amounts of glucose and oxygen to function (20% of bo ...
Physiologically-Inspired Model for the Visual Tuning Properties of
Physiologically-Inspired Model for the Visual Tuning Properties of

... where the matrix Y signifies the responses from a patch (of the position grid) from the previous layer, and where the matrix Um is a template pattern that is established by learning. The integer Nm signifies the number of non-zero elements in the matrix Um . Detectors for each particular feature, de ...
lec12
lec12

(Involuntary) and Voluntary Muscle Contractions
(Involuntary) and Voluntary Muscle Contractions

MS Word Version
MS Word Version

< 1 ... 69 70 71 72 73 74 75 76 77 ... 124 >

Neural modeling fields

Neural modeling field (NMF) is a mathematical framework for machine learning which combines ideas from neural networks, fuzzy logic, and model based recognition. It has also been referred to as modeling fields, modeling fields theory (MFT), Maximum likelihood artificial neural networks (MLANS).This framework has been developed by Leonid Perlovsky at the AFRL. NMF is interpreted as a mathematical description of mind’s mechanisms, including concepts, emotions, instincts, imagination, thinking, and understanding. NMF is a multi-level, hetero-hierarchical system. At each level in NMF there are concept-models encapsulating the knowledge; they generate so-called top-down signals, interacting with input, bottom-up signals. These interactions are governed by dynamic equations, which drive concept-model learning, adaptation, and formation of new concept-models for better correspondence to the input, bottom-up signals.
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