Generalized transfer matrix states from artificial neural networks
نویسندگان
چکیده
منابع مشابه
Estimation of Products Final Price Using Bayesian Analysis Generalized Poisson Model and Artificial Neural Networks
Estimating the final price of products is of great importance. For manufacturing companies proposing a final price is only possible after the design process over. These companies propose an approximate initial price of the required products to the customers for which some of time and money is required. Here using the existing data of already designed transformers and utilizing the bayesian anal...
متن کاملArtificial neural networks: applications in pain physiology
Artificial neural networks (ANNs) are intelligent systems that have successfully been used for prediction in different medical fields. In this study, the capability of ANN in predicting body behavior in pain-producing situations is evaluated. A three-layer back-propagation ANN is designed using MATLAB software. The inputs include the magnitude of stimulation in pain fibers, touch fibers and cen...
متن کاملArtificial neural networks: applications in pain physiology
Artificial neural networks (ANNs) are intelligent systems that have successfully been used for prediction in different medical fields. In this study, the capability of ANN in predicting body behavior in pain-producing situations is evaluated. A three-layer back-propagation ANN is designed using MATLAB software. The inputs include the magnitude of stimulation in pain fibers, touch fibers and cen...
متن کاملTransfer entropy-based feedback improves performance in artificial neural networks
The structure of the majority of modern deep neural networks is characterized by unidirectional feed-forward connectivity across a very large number of layers. By contrast, the architecture of the cortex of vertebrates contains fewer hierarchical levels but many recurrent and feedback connections. Here we show that a small, few-layer artificial neural network that employs feedback will reach to...
متن کاملClassification of cardiac patient states using artificial neural networks.
Electrocardiogram (ECG) is a nonstationary signal; therefore, the disease indicators may occur at random in the time scale. This may require the patient be kept under observation for long intervals in the intensive care unit of hospitals for accurate diagnosis. The present study examined the classification of the states of patients with certain diseases in the intensive care unit using their EC...
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: Physical Review B
سال: 2019
ISSN: 2469-9950,2469-9969
DOI: 10.1103/physrevb.99.165123