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Titel (berschirft 1, Tastenkombiation + )
Titel (berschirft 1, Tastenkombiation + )

... limits imposed by the use of only two microphones have remained an obstacle to even greater enduser benefits. ZoomControl made it possible for the first time to produce new microphone patterns by allowing an interactive exchange of data between the left and right hearing instruments. It became possi ...
Pitch Based Sound Classification
Pitch Based Sound Classification

... linear model shows superior performance, which might be explained by overfitting of the larger models. The three plots of the test errors of Figure 5 shows no improvement when using more than 7 features. The more complex models show better training error, but when it comes to test error not much is ...
Cognon Neural Model Software Verification and
Cognon Neural Model Software Verification and

... Little is known yet about how the brain can recognize arbitrary sensory patterns within milliseconds using neural spikes to communicate information between neurons. In a typical brain there are several layers of neurons, with each neuron axon connecting to ∼ 104 synapses of neurons in an adjacent la ...
PDF
PDF

COGNITIVE LEVELS OF EVOLUTION
COGNITIVE LEVELS OF EVOLUTION

... The present definition of knowledge and control can in fact also be interpreted as a definition of goals or values. The "vicarious selector" can be interpreted as an evaluation criterion for actions, which provides a general direction for the behavior of the system. The ultimate goal or value in thi ...
View Full Page PDF
View Full Page PDF

... template. This mechanism requires that harmonics of the sound produce clear peaks in the spatial pattern of BM vibration, i.e., that harmonics are “resolved” by the cochlea, but this is typically not the case for high-order harmonics because the bandwidth of cochlear filters increases with center fr ...
CURRICULUM VITAE Academic Education Academic Employment
CURRICULUM VITAE Academic Education Academic Employment

Complementary roles of basal ganglia and cerebellum in learning
Complementary roles of basal ganglia and cerebellum in learning

... complex spikes in arm-reaching movement in monkeys. The results showed that complex spike firing carries information about the target direction in the early phase of the movement, whereas it carries information about the end-point error near the end of the movement. The coding of end-point error is ...
Automatic discovery of cell types and microcircuitry from
Automatic discovery of cell types and microcircuitry from

Huntington disease models and human neuropathology: similarities
Huntington disease models and human neuropathology: similarities

... which remains asymptomatic despite expressing the HD polyQ and the referent nuclear and neuropil aggregates, supports this claim. Thus, the research on either humans or animal models must be much more convergent than it is now. The birth of the transgenic polyQ mouse, which was accepted from the sta ...
Computational Intelligence Methods
Computational Intelligence Methods

The SCHOLAR Legacy: A New Look at the Affordances of Semantic
The SCHOLAR Legacy: A New Look at the Affordances of Semantic

... The domain model represents what the learner is supposed to learn. Following tradition in psychology [e.g., Anderson, 1976; Haapasalo, 2003; Ryle, 1949; Skemp, 1979] we can accept a distinction between conceptual (or declarative) knowledge and procedural (or imperative) knowledge, i.e., the distinct ...
Crapse (2008) Corollary discharge across the animal kingdom
Crapse (2008) Corollary discharge across the animal kingdom

... stage (FIG. 1b). In studies on fish, Sperry3 coined the term “corollary discharge” (CD) to denote motor-related signals that influence sensory processing, but his conception was less specific as to where the branch from motor to sensory pathways should emerge. In this Review we compare motor-to-sens ...
Discussion and future directions
Discussion and future directions

... 2000) have shown that in order to hold memory activity for a saccades, the neural population develops excitatory connections between units with similar preferred saccade directions and inhibitory connections between units with dissimilar directions. Previous modeling results similar with ours have b ...
Cooperation and biased competition model can explain attentional
Cooperation and biased competition model can explain attentional

... target speci®c right preferred TR pool. In this situation, the attention bias set to right preferred neurons corresponds to the condition `preferred location attended', a left bias corresponds to the `nonpreferred location attended' condition. Explicit simulations of the network dynamics accurately ...
ALGORITHMICS - Universitatea de Vest din Timisoara
ALGORITHMICS - Universitatea de Vest din Timisoara

...  The solution of the problem is found by exploring the space of possible solutions; a populations of individuals (agents) is used to explore the space  The population elements are coded based on the particularities of the problem (bit strings, real value vectors, trees, graphs etc.) ...
Zwicker Tone Illusion and Noise Reduction in the Auditory System
Zwicker Tone Illusion and Noise Reduction in the Auditory System

... filters is coupled to the stereocilia of a Meddis inner-haircell model. This peripheral part was simulated by using the software package LUTEAR [19]. Its output consists of probabilities for spikes of the auditory-nerve fibers, an inhomogeneous Poisson process. In conclusion, the Zwicker tone is a p ...
Computing with Spiking Neuron Networks
Computing with Spiking Neuron Networks

... 1.4 Spiking Neuron Networks In Spiking Neuron Networks (SNNs)7 , the presence and timing of individual spikes is considered as the means of communication and neural computation. This compares with traditional neuron models where analog values are considered, representing the rate at which spikes are ...
Mechanisms for Stable, Robust, and Adaptive Development of
Mechanisms for Stable, Robust, and Adaptive Development of

... theoretical model of map organization and has strong empirical evidence, with a mean pinwheel density across four species (tree shrew, galago, cat, and ferret) statistically indistinguishable from ␲ (Kaschube et al., 2010); see data from three species in Figure 3D. To establish the pinwheel density ...
Neural representation of object orientation: A dissociation between
Neural representation of object orientation: A dissociation between

... confuse certain orientations with one another. Using fMRI, we asked whether more confusable orientations are represented more similarly in object selective cortex (LOC). We compared two widely-used measures of neural similarity: multi-voxel pattern similarity (MVP-similarity) and Repetition Suppress ...
Structured Liquids in Liquid State Machines
Structured Liquids in Liquid State Machines

Day 3 - EE Sharif
Day 3 - EE Sharif

Building silicon nervous systems with dendritic tree neuromorphs
Building silicon nervous systems with dendritic tree neuromorphs

Self-Organizing Feature Maps with Lateral Connections: Modeling
Self-Organizing Feature Maps with Lateral Connections: Modeling

Discrimination of Perfumes Using an Electronic Nose System
Discrimination of Perfumes Using an Electronic Nose System

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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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