Name
Title | ||
|---|---|---|
A novel signal diagnosis technique using pseudo complex-valued autoregressive technique |
Abstract | ||
|---|---|---|
In this paper, a new method of biomedical signal classification using complex- valued pseudo autoregressive (CAR) modeling approach has been proposed. The CAR coefficients were computed from the synaptic weights and coefficients of a split weight and activation function of a feedforward multilayer complex valued neural network. The performance of the proposed technique has been evaluated using PIMA Indian diabetes dataset with different complex-valued data normalization techniques and four different values of learning rate. An accuracy value of 81.28% has been obtained using this proposed technique. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1016/j.eswa.2010.11.005 | Expert Syst. Appl. |
Keywords | Field | DocType |
complex-valued neural network (cvnn),autoregressive model,complex-valued data (cvd),pseudo complex-valued autoregressive technique,parametric models,novel signal diagnosis technique,diabetes,activation function,parametric model,neural network,meters | Autoregressive model,Parametric model,Activation function,Computer science,Artificial intelligence,Signal classification,Artificial neural network,Pima Indian,Machine learning,Feed forward,Database normalization | Journal |
Volume | Issue | ISSN |
38 | 8 | Expert Systems With Applications |
Citations | PageRank | References |
1 | 0.36 | 19 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| A. M. Aibinu | 1 | 21 | 2.81 |
| M. J. E. Salami | 2 | 9 | 1.71 |
| A. A. Shafie | 3 | 19 | 2.28 |