Kristin Völk – Curriculum Vitae
... model of the human leg using Matlab and the Simulink and SimMechanics toolboxes. Given this model, we implemented biologically realistic muscle sensor models and a spiking neural network model with a spike-timing based learning rule. We verified that with the spiking-neural network implementation at ...
... model of the human leg using Matlab and the Simulink and SimMechanics toolboxes. Given this model, we implemented biologically realistic muscle sensor models and a spiking neural network model with a spike-timing based learning rule. We verified that with the spiking-neural network implementation at ...
Neuroembryology II_UniTsNeurosciAY1415_06a
... (expressing EGFP under the control of a promoter which specifically fires in CR-cells) into the E11.5 telencephalon, at different locations. After a few days, they studied the resulting distribution of the two markers and could prove that: (1) CR-cells are specifically generated by the cortical hem ...
... (expressing EGFP under the control of a promoter which specifically fires in CR-cells) into the E11.5 telencephalon, at different locations. After a few days, they studied the resulting distribution of the two markers and could prove that: (1) CR-cells are specifically generated by the cortical hem ...
10EI212 NEURAL NETWORKS AND FUZZY LOGIC CONTROL
... Single layer – Multi layer feed forward network – Back propagation – Learning factors Unit II Neural Networks For Control Feedback networks – Discrete time hop field networks – Schemes of neuro-control, identification and control of dynamical systems-case studies (Inverted Pendulum, Articulation Con ...
... Single layer – Multi layer feed forward network – Back propagation – Learning factors Unit II Neural Networks For Control Feedback networks – Discrete time hop field networks – Schemes of neuro-control, identification and control of dynamical systems-case studies (Inverted Pendulum, Articulation Con ...
Research Journal of Applied Sciences, Engineering and Technology 6(3): 450-456,... ISSN: 2040-7459; e-ISSN: 2040-7467
... The study presents a machine learning procedure based on SA incorporated with ANN to optimize the non-linear singular systems of radioactivity cooling, self-gravitating clouds and clusters of galaxies. The ANN mathematical modeling for singular non-linear system is performed by the linear combinatio ...
... The study presents a machine learning procedure based on SA incorporated with ANN to optimize the non-linear singular systems of radioactivity cooling, self-gravitating clouds and clusters of galaxies. The ANN mathematical modeling for singular non-linear system is performed by the linear combinatio ...
Improving CNN Performance with Min-Max Objective
... example, it is reported that increasing the number of training samples from 1M to 14M from the ImageNet dataset only improved the image classification accuracy by 1%1 . There are also methods that aim to improve training of CNN models to enhance performances. For instance, different types of activat ...
... example, it is reported that increasing the number of training samples from 1M to 14M from the ImageNet dataset only improved the image classification accuracy by 1%1 . There are also methods that aim to improve training of CNN models to enhance performances. For instance, different types of activat ...
Quiz 6 study guide
... (where motor neurons connect to skeletal muscle cells) and the junction where autonomic nervous system neurons connect to smooth cell cells in the walls of arterioles. N18. Is the graph below (Figure 46-14b from Scott Freeman et al., Biological Science [5th edition]) an example of spatial summation, ...
... (where motor neurons connect to skeletal muscle cells) and the junction where autonomic nervous system neurons connect to smooth cell cells in the walls of arterioles. N18. Is the graph below (Figure 46-14b from Scott Freeman et al., Biological Science [5th edition]) an example of spatial summation, ...
3680Lecture27
... • Clever fMRI experiment by Tong et al. (1998) – Exploit preferential responses by different regions – Present faces to one eye and buildings to the other ...
... • Clever fMRI experiment by Tong et al. (1998) – Exploit preferential responses by different regions – Present faces to one eye and buildings to the other ...
Human Vision: Electrophysiology and Psychophysics
... At one time there was a debate as to the question of whether the brain was composed of a continuous system of wires or whether it was a discontinuous network made up of individual neurons ...
... At one time there was a debate as to the question of whether the brain was composed of a continuous system of wires or whether it was a discontinuous network made up of individual neurons ...
MCB105 QUIZ 5 2016 wA
... instructive signal/ visual responses to allow alignment of visual and auditory space - their recordings showed that visual receptive fields of ICX neurons were restricted and quite similar in size to the ones observed in the OT. b) How did they open the 'gate' that prevented these findings in previo ...
... instructive signal/ visual responses to allow alignment of visual and auditory space - their recordings showed that visual receptive fields of ICX neurons were restricted and quite similar in size to the ones observed in the OT. b) How did they open the 'gate' that prevented these findings in previo ...
Neurons Firing of a neuron
... – Selectively permeable • positive ions can’t mix with negative when neuron’s “gate” is closed ...
... – Selectively permeable • positive ions can’t mix with negative when neuron’s “gate” is closed ...
Weight Features for Predicting Future Model Performance of
... the above 17 hyperparameters (Table 1). The neural networks contain from three to six convolutional layers and one fully connected layer. After each convolutional layer, we set layers for normalizing over local input regions within channels for suppressing extremely large or small outputs. We genera ...
... the above 17 hyperparameters (Table 1). The neural networks contain from three to six convolutional layers and one fully connected layer. After each convolutional layer, we set layers for normalizing over local input regions within channels for suppressing extremely large or small outputs. We genera ...
Pattern Recognition by Labeled Graph Matching
... per node is made for the sake of simplification. It is easy to generalize to several active feature cells per point.) Neural dynamics is regulated such that cellular signals are temporally unstable. Excitatory connections between neighboring cells in L m induce correlations between signals of these ...
... per node is made for the sake of simplification. It is easy to generalize to several active feature cells per point.) Neural dynamics is regulated such that cellular signals are temporally unstable. Excitatory connections between neighboring cells in L m induce correlations between signals of these ...
Technological integration and hyper-connectivity
... Complexity theory shows that there are deep underlying similarities in concepts and processes, between completely different fields (4). For instance, it helps us study the similar priniples that exist between computers (artificial networks), neurons (biological networks) and human society (such as t ...
... Complexity theory shows that there are deep underlying similarities in concepts and processes, between completely different fields (4). For instance, it helps us study the similar priniples that exist between computers (artificial networks), neurons (biological networks) and human society (such as t ...
$doc.title
... excess or unnecessary connections (and potentially nodes as well). This technique allows for robustness in nodes and connections that appear together, an effect of learning. If there are not enough occurrence ...
... excess or unnecessary connections (and potentially nodes as well). This technique allows for robustness in nodes and connections that appear together, an effect of learning. If there are not enough occurrence ...
Artificial neural networks and their application in biological and
... (Kirova et al. 2009) or the determination of the water content in leaf tissue (Goltsev et al. 2012). This proves that the development and improvement of this method for biological research is necessary and very promising (Tyystjärvi et al. 1999). Earlier ANN models Each individual neuron in the nerv ...
... (Kirova et al. 2009) or the determination of the water content in leaf tissue (Goltsev et al. 2012). This proves that the development and improvement of this method for biological research is necessary and very promising (Tyystjärvi et al. 1999). Earlier ANN models Each individual neuron in the nerv ...
Stage 2 - Sheffield Department of Computer Science
... either off or on. But now clear that there are differences: - rate of firing of neuron important, as well as on/off feature - Neuron has enormous number of input and output connections, compared to logic gates. ...
... either off or on. But now clear that there are differences: - rate of firing of neuron important, as well as on/off feature - Neuron has enormous number of input and output connections, compared to logic gates. ...
Modelling the Grid-like Encoding of Visual Space
... with respect to certain types of inputs via the parameter p. For example, setting p to higher values results in an emphasis of large changes in individual dimensions of the input vector versus changes that are distributed over many dimensions (Kerdels and Peters, 2015a). However, in the case of mode ...
... with respect to certain types of inputs via the parameter p. For example, setting p to higher values results in an emphasis of large changes in individual dimensions of the input vector versus changes that are distributed over many dimensions (Kerdels and Peters, 2015a). However, in the case of mode ...
THE JOURNAL OF COMPARATIVE NEUROLOGY 460:80–93 (2003)
... cord to verify that CRNs project onto reticulospinal neurons. Electron microscopy of the labeled CRNs axons and terminals showed that even their most central and thinnest processes are myelinated. Most of the terminals are axodendritic, with multiple asymmetric synapses, and contain round vesicles ( ...
... cord to verify that CRNs project onto reticulospinal neurons. Electron microscopy of the labeled CRNs axons and terminals showed that even their most central and thinnest processes are myelinated. Most of the terminals are axodendritic, with multiple asymmetric synapses, and contain round vesicles ( ...
lgn - cinpla
... what role does this relay center play in the visual pathway? The lateral geniculate nucleus (LGN) is placed in a prominent position in the early visual pathway. It sits between the retina and the visual cortex, acting as a relay between the two. Inserting a microelectrode into the LGN reveals that t ...
... what role does this relay center play in the visual pathway? The lateral geniculate nucleus (LGN) is placed in a prominent position in the early visual pathway. It sits between the retina and the visual cortex, acting as a relay between the two. Inserting a microelectrode into the LGN reveals that t ...
Chapter 7 part two
... An important challenge for this theory (and other theories of attention) is to explain precisely how the distributed neural populations responding to a single object ‘know’ that they are representing the same object and so should enhance each other while suppressing the neural representations of oth ...
... An important challenge for this theory (and other theories of attention) is to explain precisely how the distributed neural populations responding to a single object ‘know’ that they are representing the same object and so should enhance each other while suppressing the neural representations of oth ...
the cerebral cortex
... body), area 18, 19, parietal cortex, temporal cortex. Dorsal stream – parietal cortex (where : rods, periphery of retina, area 7) Ventral stream – temporal cortex (whatcolors, form : cones, central area of retina, area 37, inferior. temporal cortex ...
... body), area 18, 19, parietal cortex, temporal cortex. Dorsal stream – parietal cortex (where : rods, periphery of retina, area 7) Ventral stream – temporal cortex (whatcolors, form : cones, central area of retina, area 37, inferior. temporal cortex ...
A Self-Organizing Neural Network That Learns to
... to motion sequences containing occlusion and disocclusion events. The network’s learning is governed by a new set of learning and activation rules. The network develops two parallel opponent channels or "chains" of lateral excitatory connections for every resolvable motion trajectory. One channel, t ...
... to motion sequences containing occlusion and disocclusion events. The network’s learning is governed by a new set of learning and activation rules. The network develops two parallel opponent channels or "chains" of lateral excitatory connections for every resolvable motion trajectory. One channel, t ...
Prediction of Power Consumption using Hybrid System
... advantage of using ANN in comparison to the other models is that it has the ability to extract nonlinear relationships among the variables by means of ‘‘learning’’ with training data. ANN models have appreciable computational speed and their ability to handle complex non-linear functions even when e ...
... advantage of using ANN in comparison to the other models is that it has the ability to extract nonlinear relationships among the variables by means of ‘‘learning’’ with training data. ANN models have appreciable computational speed and their ability to handle complex non-linear functions even when e ...
