Fundamentals of Computational Neuroscience
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Fundamentals of Computational Neuroscience
Third Edition
Trappenberg, Thomas P.
Oxford University Press
12/2022
416
Mole
Inglês
9780192869364
15 a 20 dias
894
Descrição não disponível.
1: Introduction
Basic Neurons
2: Neurons and conductance-based models
3: Simplified neuron and population models
4: Associators and synaptic plasiticity
Basic Networks
5: Cortical organizations and simple networks
6: Feed-forward mapping networks
7: Cortical feature maps and competitive population coding
8: Recurrent associative networks and episodic memory
System-Level Models
9: Modular networks, motor control, and reinforcement learning
10: The cognitive brain
A: Some useful mathematics
B: Numerical calculus
C: Basic probability theory
D: Basic information theory
E: A brief introduction to MATLAB
Basic Neurons
2: Neurons and conductance-based models
3: Simplified neuron and population models
4: Associators and synaptic plasiticity
Basic Networks
5: Cortical organizations and simple networks
6: Feed-forward mapping networks
7: Cortical feature maps and competitive population coding
8: Recurrent associative networks and episodic memory
System-Level Models
9: Modular networks, motor control, and reinforcement learning
10: The cognitive brain
A: Some useful mathematics
B: Numerical calculus
C: Basic probability theory
D: Basic information theory
E: A brief introduction to MATLAB
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
1: Introduction
Basic Neurons
2: Neurons and conductance-based models
3: Simplified neuron and population models
4: Associators and synaptic plasiticity
Basic Networks
5: Cortical organizations and simple networks
6: Feed-forward mapping networks
7: Cortical feature maps and competitive population coding
8: Recurrent associative networks and episodic memory
System-Level Models
9: Modular networks, motor control, and reinforcement learning
10: The cognitive brain
A: Some useful mathematics
B: Numerical calculus
C: Basic probability theory
D: Basic information theory
E: A brief introduction to MATLAB
Basic Neurons
2: Neurons and conductance-based models
3: Simplified neuron and population models
4: Associators and synaptic plasiticity
Basic Networks
5: Cortical organizations and simple networks
6: Feed-forward mapping networks
7: Cortical feature maps and competitive population coding
8: Recurrent associative networks and episodic memory
System-Level Models
9: Modular networks, motor control, and reinforcement learning
10: The cognitive brain
A: Some useful mathematics
B: Numerical calculus
C: Basic probability theory
D: Basic information theory
E: A brief introduction to MATLAB
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
