Interpolation representation of feedforward neural networks
نویسندگان
چکیده
منابع مشابه
Optimal Genetic Representation of Complete Strictly-Layered Feedforward Neural Networks
The automatic evolution of neural networks is both an attractive and a rewarding task. The connectivity matrix is the most common way of directly encoding a neural network for the purpose of genetic optimization. However, this representation presents several disadvantages mostly stemming from its inherent redundancy and its lack of robustness. We propose a novel representation scheme for encodi...
متن کاملImage Interpolation using Feedforward Neural Network
As various kinds of output devices emerged, such as highresolution printers or a display of PDA(Personal Digital Assistant), the importance of high-quality resolution conversion has been increasing. This paper proposes a new method for enlarging image with high quality. One of the largest problems on image enlargement is the exaggeration of the jaggy edges. To remedy this problem, we propose a ...
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: Mathematical and Computer Modelling
سال: 2003
ISSN: 0895-7177
DOI: 10.1016/s0895-7177(03)00088-8