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Titlebook: Neural Network Simulation Environments; Josef Skrzypek Book 1994 Springer Science+Business Media New York 1994 algorithms.development.inte

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Marwan A. Jabri,Edward A. Tinker,Laurens Leerinkn of stars; their end and how this is manifested; how we think galaxies are created from matter we have yet to discover and why we believe the most energetic particles cannot come from the most distant universe. During the IV Escuela Mexicana de Astrof´ ?sica (EMA-2005), held in the beautiful coloni
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n of stars; their end and how this is manifested; how we think galaxies are created from matter we have yet to discover and why we believe the most energetic particles cannot come from the most distant universe. During the IV Escuela Mexicana de Astrof´ ?sica (EMA-2005), held in the beautiful coloni
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NEXUS: A Neural Simulator for Integrating Top-Down and Bottom-Up Modeling,. A unique aspect of NEXUS is that it is particularly suited for simulating hybrid neural models (i.e. systems integrating different modeling paradigms and/or architectures..) NEXUS is designed for large-scale simulations, and to facilitate model development, testing and analysis it incorporates sev
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,SWIM — A Simulation Environment for Realistic Neural Network Modeling,ll parameters involved. We have designed a specification language for this purpose. A simulation environment based on this language has been implemented, including tools for running the actual simulations on either a Unix workstation, a CRAY supercomputer, or a Connection Machine (CM, a massively pa
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NSL Neural Simulation Language,r describing neural networks, an interactive command interpreter, and powerful visualization tools. The simulator is designed and implemented using object-oriented programming methodologies. NSL provides a simulation platform for different types of applications, including both biological and artific
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CAJAL: A Simulator for Neurobiological Networks,rks. In one class are the many simulators for artificial neural networks and connectionist applications. In the other, are the relatively few simulators for real biological neural networks and neurobiology applications. Although the two classes share certain surface characteristics (e.g. methods of
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NBC: A Workstation for Biological Neural Network Simulation, little about computer sciences. NBC provides two neuron simulation levels: a simple, fast phenomenological one in which membrane potential and threshold are included, and a more sophisticated, slower one, based on conductance variations in different ionic channels. NBC enables the simulation of bio
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NeMoSys: A System for Realistic Single Neuron Modeling, neurons with complex geometries at the level of currents and voltages in individual branches. Neurons are represented as binary branched tree structures, where branches are constructed from linear strings of compartments. The program is set up to allow the user to simulate typical electrophysiologi
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