• Study Resource
  • Explore
    • Arts & Humanities
    • Business
    • Engineering & Technology
    • Foreign Language
    • History
    • Math
    • Science
    • Social Science

    Top subcategories

    • Advanced Math
    • Algebra
    • Basic Math
    • Calculus
    • Geometry
    • Linear Algebra
    • Pre-Algebra
    • Pre-Calculus
    • Statistics And Probability
    • Trigonometry
    • other →

    Top subcategories

    • Astronomy
    • Astrophysics
    • Biology
    • Chemistry
    • Earth Science
    • Environmental Science
    • Health Science
    • Physics
    • other →

    Top subcategories

    • Anthropology
    • Law
    • Political Science
    • Psychology
    • Sociology
    • other →

    Top subcategories

    • Accounting
    • Economics
    • Finance
    • Management
    • other →

    Top subcategories

    • Aerospace Engineering
    • Bioengineering
    • Chemical Engineering
    • Civil Engineering
    • Computer Science
    • Electrical Engineering
    • Industrial Engineering
    • Mechanical Engineering
    • Web Design
    • other →

    Top subcategories

    • Architecture
    • Communications
    • English
    • Gender Studies
    • Music
    • Performing Arts
    • Philosophy
    • Religious Studies
    • Writing
    • other →

    Top subcategories

    • Ancient History
    • European History
    • US History
    • World History
    • other →

    Top subcategories

    • Croatian
    • Czech
    • Finnish
    • Greek
    • Hindi
    • Japanese
    • Korean
    • Persian
    • Swedish
    • Turkish
    • other →
 
Profile Documents Logout
Upload
Neural Preprocessing and Control of Reactive Walking
Neural Preprocessing and Control of Reactive Walking

... Although some of this research has been concentrated on the generation of a reactive behavior of walking machines, it has been restricted only to a few of such reactive behaviors. However, from this research, there are only few examples where different behaviors have been implemented in one machine ...
Bissonette Gregory B, Gentry Ronny N, Padmala Srikanth, Pessoa L
Bissonette Gregory B, Gentry Ronny N, Padmala Srikanth, Pessoa L

JudgeD: A Probabilistic Datalog with Dependencies
JudgeD: A Probabilistic Datalog with Dependencies

... 1996); Markov Logic Networks (Richardson and Domingos 2006); constraint logic programming for probabilistic knowledge, know as CLP(BN ), (Costa et al. 2002); probabilistic Datalog, known as pD, (Fuhr 2000); and ProbLog (De Raedt, Kimmig, and Toivonen 2007). In these logics probabilities can be attac ...
DU35687693
DU35687693

... phenomena, events, actions, processes, to certain well defined sets of individuality. Pattern recognition theory is divided into two categories: supervised and unsupervised learning. Classifies are part of the supervised learning, using information about the membership of an object to a set in order ...
Biologically Plausible Error-driven Learning using Local Activation
Biologically Plausible Error-driven Learning using Local Activation

Efficient Event-Driven Simulation of Large Networks of Spiking
Efficient Event-Driven Simulation of Large Networks of Spiking

... But learning is guided by neural activities, which in turn are governed by the acquired synapses. Hence, for these models to make a leap toward a realistic description of learning, as it results from the dynamical interaction with the environment, a mechanism has to be incorporated in the model to d ...
Neurons, Brain Chemistry, and Neurotransmission
Neurons, Brain Chemistry, and Neurotransmission

... The billions of neurons that make up the brain coordinate thought, behavior, homeostasis, and more. How do all these neurons pass and receive information? Neurons convey information by transmitting messages to other neurons or other types of cells, such as muscles. The following discussion focuses o ...
Brief Survey on Computational Solutions for Bayesian Inference
Brief Survey on Computational Solutions for Bayesian Inference

... From 2006 to 2011, the research group lead by Professor Viktor Prasanna at the University of Southern California produced a vast body of work contributing with solutions for the implementation of exact inference in multi/manycore CPUs and GPUs. Starting in 2006, Namasivayam et al. presented a study ...
Basal Ganglia Outputs Map Instantaneous Position Coordinates
Basal Ganglia Outputs Map Instantaneous Position Coordinates

... 2014). Some neurons increased firing when the mouse was tilted to its left and decreased firing when tilted to its right, whereas other neurons displayed the opposite pattern. During postural disturbances, the motor system must generate continuously varying outputs to oppose the effects of tilt on t ...
Ambient Noise Reduction for Portable PC`s and
Ambient Noise Reduction for Portable PC`s and

... are wanted signals? What about the game's background music, not to mention the dog? Clearly, in the above complex situations, the definitions of wanted signals and unwanted noise are dependent upon human understanding of the context which, as of this writing, computer software cannot analyze and und ...
Auto-structure of presynaptic activity defines postsynaptic firing
Auto-structure of presynaptic activity defines postsynaptic firing

Pierre Berthet Computational Modeling of the Basal Ganglia – Functional Pathways
Pierre Berthet Computational Modeling of the Basal Ganglia – Functional Pathways

FREE Sample Here
FREE Sample Here

... b) continuous conduction of graded potentials. c) changing the frequency of impulses sent to sensory centers. d) propagation action potential in both directions. e) modifying the length of the refractory period. Answer: c Difficulty: Medium Study Objective 1: SO 12.3 Describe the types of electrical ...
Introduction to Neural Networks "Energy" and attractor networks
Introduction to Neural Networks "Energy" and attractor networks

Two Types of Neurons in the Primate Globus
Two Types of Neurons in the Primate Globus

... well as between pro- (204 ± 56 ms) and antisaccades (230 ± 51 ms, P < 0.05). There was also a significant interaction between the main factors (P < 0.05), indicating that the difference in latency between the 2 saccade tasks was statistically greater in the Deliberate condition than in the Immediate ...
The Involvement of Recurrent Connections in Area CA3 in
The Involvement of Recurrent Connections in Area CA3 in

... their resting potentials), ␶ and ␶⬘ are the membrane time constants for pyramidal neurons and the inhibitory cell, respectively, Jij is the strength of the connection from neuron j to neuron i, h is the efficacy of inhibition, w represents the strength of the excitatory connection from any one pyram ...
Artificial Intelligence Chapter 7 - Computer Science
Artificial Intelligence Chapter 7 - Computer Science

... encodings of the masses and speeds • Generally we would have one output unit for each class, with activation 1 for ‘yes’ and 0 for ‘no’ • With just two classes here, we can have just one output unit, with activation 1 for ‘fighter’ and 0 for ‘bomber’ (or vice versa) • The simplest network to try fir ...
Impact of correlated inputs to neurons
Impact of correlated inputs to neurons

Slides - Translational Neuromodeling Unit
Slides - Translational Neuromodeling Unit

... fMRI - physics and physiology ...
Predominance of Movement Speed Over Direction in Neuronal
Predominance of Movement Speed Over Direction in Neuronal

... to motor-cortical activity have been previously studied using voluntary movement paradigms that broadly fall into 2 categories: (1) “event-related” tasks (Pfurtscheller and Lopes da Silva 1999), where subjects make repetitive, short-duration movements of up to a few seconds, for example, after a “go ...
discrete variational autoencoders
discrete variational autoencoders

Dopamine: generalization and bonuses
Dopamine: generalization and bonuses

Extra-Classical Tuning Predicts Stimulus
Extra-Classical Tuning Predicts Stimulus

... up-sampling in each dimension using a cubic spline. To validate each GLM STRF as a model for auditory tuning, we used the STRF to predict 10 spike trains in response to song and noise samples that were played while recording but were not used in the STRF estimation. We then compared the predicted re ...
Human Economic Choice as Costly Information Processing
Human Economic Choice as Costly Information Processing

... choice between the two lotteries, certain and uncertain, is now determined by the comparison of these two values. Neural studies have focused on the impact of administered reward and isolated areas of the nucleus accumbens and mesial prefrontal cortex associated with the processing of gains and the ...
Neuronal activity in human primary visual cortex correlates with
Neuronal activity in human primary visual cortex correlates with

< 1 ... 10 11 12 13 14 15 16 17 18 ... 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.
  • studyres.com © 2025
  • DMCA
  • Privacy
  • Terms
  • Report