Name
Title | ||
|---|---|---|
In search of an optimization technique for Artificial Neural Network to classify abnormal heart sounds |
Abstract | ||
|---|---|---|
Artificial Neural Network (ANN) finds use in classification of heart sounds for its discriminative training ability and easy implementation. The selection of number of nodes for an ANN remains an important issue as an overparameterized ANN gets trained along with the redundant information that results in poor validation. Also a larger network means more computational expense, resulting more hardware and time related cost. Therefore, a compact and optimum design of neural network is needed towards real-time detection of pathological patterns, if any from heart sound signals. This work attempts to (i) design a compact form of output layer with less number of nodes than output classes, (ii) select a set of input features that are effective for identification of heart sound signals using Singular Value Decomposition (SVD), QR factorization with column pivoting (QRcp) and Fisher's F-ratio, (iii) make certain optimum selection of nodes in the hidden layer for a more effective ANN structure using SVD and (iv) select and prune weights based on the concept of local relative sensitivity index (LRSI) for empirically chosen overparameterized ANN structure for phonocardiogram (PCG) classification. It is observed that the proposed techniques perform better in terms of reduction of model residues and time complexity for classifying 12 different pathological cases and normal heart sound. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1016/j.asoc.2008.04.010 | Appl. Soft Comput. |
Keywords | Field | DocType |
optimization technique,ann structure,certain optimum selection,hidden layer,f -ratio,ann,compact form,artificial neural network,classification of heart diseases,effective ann structure,qrcp,normal heart sound,heart sound signal,svd,phonocardiogram,heart sound,different pathological case,pruning,overparameterized ann,abnormal heart,optimization,singular value decomposition,neural network,real time,f ratio,time complexity,qr factorization,sensitivity index | Phonocardiogram,Computer science,Artificial intelligence,Time complexity,Artificial neural network,Discriminative model,QR decomposition,Heart sounds,Singular value decomposition,Mathematical optimization,Pattern recognition,Abnormal heart sounds,Machine learning | Journal |
Volume | Issue | ISSN |
9 | 1 | Applied Soft Computing Journal |
Citations | PageRank | References |
13 | 0.74 | 12 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Samit Ari | 1 | 66 | 8.28 |
| Goutam Saha | 2 | 255 | 23.17 |