Neuralsyns:A Novel Tool for Simulating Large Neuronal Networks With Complex Architectures
نویسندگان
چکیده
منابع مشابه
BOSAM: A topology visualisation tool for large-scale complex networks
Many information and communications networks are very large and they exhibit extremely complex structures. Here we propose a topology visualisation tool, called the bitmap of sorted adjacency matrix (BOSAM), which illustrates the connectivity information of a network as a bitmap image. We show that by using carefully designed rules to sort network node in specific orders, the produced bitmaps a...
متن کاملSimulating Large-scale Networks with Analytical Models
Discrete-event simulation of computer networks has significant scalability issues, which makes simulating large-scale networks problematic. We propose a high-level abstraction modeling network domains, interdomain links and traffic with highly scalable analytical models, which is much more efficient but slightly less accurate than node-by-node models. Thus, simulation scenarios containing sever...
متن کاملSimulating Asynchronous Architectures on Transputer Networks
Recently, there has been a resurgence of interest in asynchronous design techniques due to the potential of asynchronous logic for higher performance, power ef-ciency and immunity from clock-related timing problems. Occam, a CSP-based parallel language provides for the rapid development of asynchronous architectural simulation models which may then be executed on a transputer network to achieve...
متن کاملSimulating Artificial Neural Networks on Parallel Architectures
Parallelism and distribution have been considered the key features of neural processing. The term parallel distributed processing is even used as a synonym for ar-tiicial neural networks. Nevertheless, the actual implementations are still in search of the appropriate model to "naturally represent" neural computing. And the-nal judgement is always given in performance gures { keeping the paralle...
متن کاملSimulating Large Random Boolean Networks
The Kauffman N -K, or random boolean network, model is an important tool for exploring the properties of large scale complex systems. There are computational challenges in simulating large networks with high connectivities. We describe some high-performance data structures and algorithms for implementing large-scale simulations of the random boolean network model using various storage types pro...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Frontiers in Neuroscience
سال: 2009
ISSN: 1662-453X
DOI: 10.3389/conf.neuro.01.2009.11.045