Name
Abstract | ||
|---|---|---|
Neural networks (NNs) are proposed for approximating the Average Likelihood Ratio (ALR). The detection of gaussian targets with gaussian autocorrelation function and unknown one-lag correlation coefficient, ρs, in Additive White Gaussian Noise (AWGN) is considered. After proving the low robustness of the likelihood ratio (LR) detector with respect to ρs, the ALR detector assuming a uniform distribution of this parameter in [0,1] has been studied. Due to the complexity of the involved integral, two NN based solutions are proposed. Firstly, single Multi-Layer Perceptrons (MLPs) are trained with target patterns with ρs varying in [0,1]. This scheme outperforms the LR detector designed for a fixed value of ρs. MLP with 17 hidden neurons is proposed as a solution. Then, two MLPs trained with target patterns with ρs varying in [0,0.5] and [0.5,1], respectively, are combined. This scheme outperforms the single MLP and allows to determine a solution of compromise between complexity and approximation error. A detector composed of MLPs with 17 and 8 hidden units each one is proposed. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/11875581_36 | IDEAL |
Keywords | Field | DocType |
single mlp,alr detector,target pattern,additive white gaussian noise,single multi-layer perceptrons,gaussian autocorrelation function,composite hypothesis test,hidden neuron,gaussian target,neural network detector,lr detector,hidden unit,multi layer perceptron,hypothesis test,autocorrelation function,approximation error,uniform distribution,likelihood ratio,neural network | Pattern recognition,White noise,Gaussian,Artificial intelligence,Gaussian process,Artificial neural network,Gaussian noise,Additive white Gaussian noise,Detector,Perceptron,Mathematics | Conference |
Volume | ISSN | ISBN |
4224 | 0302-9743 | 3-540-45485-3 |
Citations | PageRank | References |
4 | 0.47 | 11 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| D. Mata Moya | 1 | 17 | 3.28 |
| P. Jarabo-Amores | 2 | 29 | 4.10 |
| raul vicenbueno | 3 | 55 | 7.55 |
| Manuel Rosa-Zurera | 4 | 192 | 36.27 |
| Lopez-Ferreras, F. | 5 | 104 | 9.93 |