Feedforward neural networks for compound signals
نویسندگان
چکیده
منابع مشابه
On Interference of Signals and Generalization in Feedforward Neural Networks
This paper studies how the generalization ability of neurons can be affected by mutual processing of different signals. This study is done on the basis of a feedforward artificial neural network, that is used here as a model of the very basic processes in a network of biological neurons. The mutual processing of signals, called here an interference of signals, can possibly be a good model of pa...
متن کاملFeedforward networks with fuzzy signals
The paper discusses feedforward neural networks with fuzzy signals. We analyze the feedforward phase and show some properties of the output function. Then we present a backpropagation like adaptation algorithm for crisp weights, thresholds and neuron slopes of the multilayer network with sigmoidal transfer functions. We provide theoretical justification for the adaptation formulas. The results ...
متن کاملFeedforward Neural Networks
Here x is an input, y is a “label”, v ∈ Rd is a parameter vector, and f(x, y) ∈ Rd is a feature vector that corresponds to a representation of the pair (x, y). Log-linear models have the advantage that the feature vector f(x, y) can include essentially any features of the pair (x, y). However, these features are generally designed by hand, and in practice this is a limitation. It can be laborio...
متن کاملFeedforward Neural Networks
Feedforward neural networks have been used to perform classifications and to learn functional mappings. This paper compares human performance to feedforward neural networks using back propagation in generating functional relationships from limited data. Many business judgments are made in situations where decision makers are required to infer relationships porn partial, incomplete, and conflict...
متن کاملEvolving Neural Feedforward Networks
For many practical problem domains the use of neural networks has led to very satisfactory results. Nevertheless the choice of an appropriate, problem specific network architecture still remains a very poorly understood task. Given an actual problem, one can choose a few different architectures, train the chosen architectures a few times and finally select the architecturewith the best behaviou...
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: Theoretical Computer Science
سال: 2011
ISSN: 0304-3975
DOI: 10.1016/j.tcs.2011.05.046