Description Logics
... consisting of the concept names in NC as unary predicates and the role names in NR as binary predicates) can be viewed as an ALC interpretation and vice versa. Intuitively, the first-order formula τx (C) describes all domain elements d ∈ ∆I that make τx (C) true if x is replaced by them. It is easy ...
... consisting of the concept names in NC as unary predicates and the role names in NR as binary predicates) can be viewed as an ALC interpretation and vice versa. Intuitively, the first-order formula τx (C) describes all domain elements d ∈ ∆I that make τx (C) true if x is replaced by them. It is easy ...
Mobile application of artificial intelligence to vital signs
... population-based diagnostic flows, we could provide more accurate, cost efficient and effective solution, in order to answer many population-based problems of modern health care systems. The framework developed by this research addresses elements that are common to current mobile health monitoring s ...
... population-based diagnostic flows, we could provide more accurate, cost efficient and effective solution, in order to answer many population-based problems of modern health care systems. The framework developed by this research addresses elements that are common to current mobile health monitoring s ...
Reconciling Simplicity and Likelihood Principles in Perceptual
... The first question invites an easy answer: that the perceptual organization is made as simple as possible. But, taken at face value, this means that a very simple organization (perhaps perceiving the distal scene to be a uniform, unstructured field) would always be a preferred organization. This pos ...
... The first question invites an easy answer: that the perceptual organization is made as simple as possible. But, taken at face value, this means that a very simple organization (perhaps perceiving the distal scene to be a uniform, unstructured field) would always be a preferred organization. This pos ...
Corina Wirth and Hans
... against the bath electrode. To improve the signal-to-noise ratio, the traces were averaged (n ⫽ 15–20). Because spike activity can be detected with MEA electrodes at distances of ⱕ100 m (Egert et al. 2002), we assume that each electrode records additional weak signals from neurons located close to ...
... against the bath electrode. To improve the signal-to-noise ratio, the traces were averaged (n ⫽ 15–20). Because spike activity can be detected with MEA electrodes at distances of ⱕ100 m (Egert et al. 2002), we assume that each electrode records additional weak signals from neurons located close to ...
Varieties of Analogical Reasoning
... Pre-hoc analogy involves missing data, ill-defined goals, and incomplete specification of parameters (Klein, 1987). A major gap is that AI models of analogy are typically not integrated with models of problem solving (Holyoak, 2008a). Models of analogy that construct mappings based on the matching o ...
... Pre-hoc analogy involves missing data, ill-defined goals, and incomplete specification of parameters (Klein, 1987). A major gap is that AI models of analogy are typically not integrated with models of problem solving (Holyoak, 2008a). Models of analogy that construct mappings based on the matching o ...
Canceling Planned Action: An fMRI Study of
... Subjects performed eight runs of a saccade countermanding task (Fig. 2). The order of the trials was counterbalanced and yielded a total of 240 GO, 80 CATCH and 80 STOP trials with an equal number of right and left targets. No more than three STOP trials could occur in a row. The intertrial interval ...
... Subjects performed eight runs of a saccade countermanding task (Fig. 2). The order of the trials was counterbalanced and yielded a total of 240 GO, 80 CATCH and 80 STOP trials with an equal number of right and left targets. No more than three STOP trials could occur in a row. The intertrial interval ...
Efficient Deep Feature Learning and Extraction via StochasticNets
... non-adjacent layers. Second, in a deep feed-forward neural network, there can be no neural connections between neurons on the same layer. Therefore, to enforce these two properties, p(i → j) = 0 when l(i) 6= l(j) + 1 where l(i) encodes the layer number associated to the node i. An example random gra ...
... non-adjacent layers. Second, in a deep feed-forward neural network, there can be no neural connections between neurons on the same layer. Therefore, to enforce these two properties, p(i → j) = 0 when l(i) 6= l(j) + 1 where l(i) encodes the layer number associated to the node i. An example random gra ...
Review Reward, Motivation, and Reinforcement Learning
... temporal difference (TD) learning model of Pavlovian conditioning uses such relationships to allow the critic to solve its own temporal credit assignment problem. That is, the value V(b) of state b depends on distal rewards, i.e., rewards that the rat does not receive immediately following the actio ...
... temporal difference (TD) learning model of Pavlovian conditioning uses such relationships to allow the critic to solve its own temporal credit assignment problem. That is, the value V(b) of state b depends on distal rewards, i.e., rewards that the rat does not receive immediately following the actio ...
Drums and Bass Interlocking - Music Technology Group
... implementation of algorithms to compose music. Previous to the existence of computers, musicians already used algorithms to compose music (e.g. Mozart, Cage), and these could obviously also be implemented with computers. We must difference between using algorithms to compose a complete music piece a ...
... implementation of algorithms to compose music. Previous to the existence of computers, musicians already used algorithms to compose music (e.g. Mozart, Cage), and these could obviously also be implemented with computers. We must difference between using algorithms to compose a complete music piece a ...
Big Data Analytics Using Neural networks
... Here, there can be any number of input, hidden and output layers connected in the network. In simplest terms, neural network, initially, makes random guesses and sees how far its answers are from the actual answers and makes an appropriate adjustment to its node-connection weights. ...
... Here, there can be any number of input, hidden and output layers connected in the network. In simplest terms, neural network, initially, makes random guesses and sees how far its answers are from the actual answers and makes an appropriate adjustment to its node-connection weights. ...
A computational model of action selection in the basal ganglia. I. A
... central nervous system. The overall activity level of the neural representation of a given action may determine its salience or propensity to be selected for execution, as proposed by Koechlin and Burnod (1996). Rather than dealing directly with the neural codes for each action, we propose that the ...
... central nervous system. The overall activity level of the neural representation of a given action may determine its salience or propensity to be selected for execution, as proposed by Koechlin and Burnod (1996). Rather than dealing directly with the neural codes for each action, we propose that the ...
Spike-based Winner-Take-All Computation in a Multi
... and Poisson spike trains under which parameters the decision of the winner is optimal, that is it makes use of all information available in the input spikes. For inputs of regular rates the winner can be selected with only one inter-spike interval. For inputs of Poisson rates, the performance of the ...
... and Poisson spike trains under which parameters the decision of the winner is optimal, that is it makes use of all information available in the input spikes. For inputs of regular rates the winner can be selected with only one inter-spike interval. For inputs of Poisson rates, the performance of the ...
Reconciling simplicity and likelihood principles in perceptual
... initiated by Helmholtz (1910/1962), advocates the likelihood principle: that sensory input will be organized into the most probable distal object or event consistent with that input. The second, initiated by Wertheimer and developed by other Gestalt psychologists, advocates what Pomerantz and Kubovy ...
... initiated by Helmholtz (1910/1962), advocates the likelihood principle: that sensory input will be organized into the most probable distal object or event consistent with that input. The second, initiated by Wertheimer and developed by other Gestalt psychologists, advocates what Pomerantz and Kubovy ...
Single-Trial Decoding of Visual Attention from Local Field Potentials
... epoch (cue onset to 400 ms after cue onset), 58% for the attentional epoch (800 –1200 ms after cue onset), and 75% for the saccade epoch (⫺200 to ⫹200 ms after saccade onset). In the mid-␥ band (␥M: 60 –120 Hz), cue decoding reached 48%, attention decoding 44%, and saccade decoding 50%. For frequenc ...
... epoch (cue onset to 400 ms after cue onset), 58% for the attentional epoch (800 –1200 ms after cue onset), and 75% for the saccade epoch (⫺200 to ⫹200 ms after saccade onset). In the mid-␥ band (␥M: 60 –120 Hz), cue decoding reached 48%, attention decoding 44%, and saccade decoding 50%. For frequenc ...
Enhanced Modulation of Neuronal Activity during
... Keywords: antisaccade, globus pallidus, inactivation, physiology, primate ...
... Keywords: antisaccade, globus pallidus, inactivation, physiology, primate ...
Input evoked nonlinearities in silicon dendritic circuits
... Fig. 2. Simplified schematics of the synaptic circuits in each compartment. The top left schematic shows the circuit for AMPA synapse, which is modeled as a low-pass filter (LPF). The top right schematic shows the NMDA synapse, which has a relatively long time constant and is sensitive to both the l ...
... Fig. 2. Simplified schematics of the synaptic circuits in each compartment. The top left schematic shows the circuit for AMPA synapse, which is modeled as a low-pass filter (LPF). The top right schematic shows the NMDA synapse, which has a relatively long time constant and is sensitive to both the l ...
“left or right” Decision-making beyond
... simulate decision-making and related brain activity using computational models, naturally touches delicate philosophical issues. Yet, we will dismiss this matter here by confining our study to choices solely attributable to the sensory input to - and the assumed properties of - the decision-making u ...
... simulate decision-making and related brain activity using computational models, naturally touches delicate philosophical issues. Yet, we will dismiss this matter here by confining our study to choices solely attributable to the sensory input to - and the assumed properties of - the decision-making u ...
Translation of Aggregate Programs to Normal Logic Programs
... The fixpoints of are called partial stable fixpoints of . The stable operator is monotone in the precision order and has a least fixpoint, called the well-founded fixpoint of % and denoted with :<; . This fixpoint can be computed by transfinite ! . Of iteration of starting from the bottom e ...
... The fixpoints of are called partial stable fixpoints of . The stable operator is monotone in the precision order and has a least fixpoint, called the well-founded fixpoint of % and denoted with :<; . This fixpoint can be computed by transfinite ! . Of iteration of starting from the bottom e ...
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