منابع مشابه
Parallel Hopfield Networks
We introduce a novel type of neural network, termed the parallel Hopfield network, that can simultaneously effect the dynamics of many different, independent Hopfield networks in parallel in the same piece of neural hardware. Numerically we find that under certain conditions, each Hopfield subnetwork has a finite memory capacity approaching that of the equivalent isolated attractor network, whi...
متن کاملParallel Evaluation of Hopfield Neural Networks
Among the large number of possible optimization algorithms, Hopfield Neural Networks (HNN) propose interesting characteristics for an in-line use. Indeed, this particular optimization algorithm can produce solutions in brief delay. These solutions are produced by the HNN convergence which was originally defined for a sequential evaluation of neurons. While this sequential evaluation leads to lo...
متن کاملNeutral Facial Image Recognition Using Parallel Hopfield Neural Networks
This paper presents an approach to perform neutral facial image recognition through facial expression image. The differential of this work is the previous images processing. First, the dimension is reduced. Next, the image is sliced into gray levels, from the most significant bits to the less significant bits. Finally, eight parallel hopfield neural networks are applied, one for each gray level...
متن کاملParallel Implementations of Hopfield Neural Networks On GPU
In recent years the multi-cores and General-Purpose GPU (GPGPU) architectures have become general platforms for various of parallel applications, with lots of parallel algorithms being proposed for this interesting persperctive. In this report, we study and develop a particular kind of artificial neural network (ANN), in hopfield model, to solve some optimization problems, since it has a highly...
متن کاملNon-monotonic Hopfield Networks
We investigate the retrieval phase diagrams of an asynchronous fully-connected attractor network with non-monotonic transfer function by means of a mean-field approximation. We find for the noiseless zero-temperature case that this non-monotonic Hopfield network can store more patterns than a network with monotonic transfer function investigated by Amit et al. Properties of retrieval phase diag...
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ژورنال
عنوان ژورنال: Neural Computation
سال: 2009
ISSN: 0899-7667,1530-888X
DOI: 10.1162/neco.2008.03-07-496