MLP Based Tan-Sigmoid Activation Function for Cardiac Activity Monitoring
نویسندگان
چکیده
منابع مشابه
Multi-Valued Neuron with Sigmoid Activation Function for Pattern Classification
Multi-Valued Neuron (MVN) was proposed for pattern classification. It operates with complex-valued inputs, outputs, and weights, and its learning algorithm is based on error-correcting rule. The activation function of MVN is not differentiable. Therefore, we can not apply backpropagation when constructing multilayer structures. In this paper, we propose a new neuron model, MVN-sig, to simulate ...
متن کاملPopulation dynamics: Variance and the sigmoid activation function
This paper demonstrates how the sigmoid activation function of neural-mass models can be understood in terms of the variance or dispersion of neuronal states. We use this relationship to estimate the probability density on hidden neuronal states, using non-invasive electrophysiological (EEG) measures and dynamic casual modelling. The importance of implicit variance in neuronal states for neural...
متن کاملSigmoid Function Based Dynamic Threshold Scheme for Shared-Buffer Switches
Buffer space in packet switching nodes is an important network resource. Shared buffer switches are prone to high packet losses and unfair use of buffer space. The use of a buffer management scheme is necessary to overcome these problems. This paper investigates the performance of Sigmoid Function Threshold scheme by means of simulations. This scheme regulates the usage of shared buffer space b...
متن کاملEvaluation of Cardiac Function in Patients with Brain Death using Advanced Hemodynamic Monitoring
Background: Studies on hemodynamic changes in brain death are in vitro and in animal studies. And very few studies have been done on the hemodynamic changes of brain death. The aim of this study was to use advanced hemodynamic monitoring with echocardiography for evaluation of donated heart and to evaluate the moment by moment brain death patients with advanced hemodynamic monitoring tools and ...
متن کاملGeoid Determination Based on Log Sigmoid Function of Artificial Neural Networks: (A case Study: Iran)
A Back Propagation Artificial Neural Network (BPANN) is a well-known learning algorithmpredicated on a gradient descent method that minimizes the square error involving the networkoutput and the goal of output values. In this study, 261 GPS/Leveling and 8869 gravity intensityvalues of Iran were selected, then the geoid with three methods “ellipsoidal stokes integral”,“BPANN”, and “collocation” ...
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: MATEC Web of Conferences
سال: 2019
ISSN: 2261-236X
DOI: 10.1051/matecconf/201925503005