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Bożena Kunka Tutor: dr inż.. Jan Matuszewski The Application of Neural Networks in Radar Signals Recognition.

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Presentation on theme: "Bożena Kunka Tutor: dr inż.. Jan Matuszewski The Application of Neural Networks in Radar Signals Recognition."— Presentation transcript:

1 Bożena Kunka Tutor: dr inż.. Jan Matuszewski The Application of Neural Networks in Radar Signals Recognition

2 Neural Networks - application  Construction of a arificial neuron bases on biological nerve cell 2/12The Application of Neural Networks in Radar Signals Recognition  Issues of recognition are currently the most often used of neural networks application 1. 1g  Applying the neural networks in radioelectronics gives enormous possibilities of real-time information processing

3 McCulloch-Pitts Neuron Model input values (signals) vector weighted coefficients vector total neuron excitation signal value at the neuron’s output neuron activation function The Application of Neural Networks in Radar Signals Recognition3/12

4 Neuron activation functions  linear function  sigmoidal function  step function 4/12The Application of Neural Networks in Radar Signals Recognition

5 Multilayer Perceptron 5/12The Application of Neural Networks in Radar Signals Recognition

6 Learning the Neural Networks 6/12The Application of Neural Networks in Radar Signals Recognition  with a teacher  without a teacher - basing on the learning set the network learns the proper operation - applied when the network responses are not known

7 Minimum Distance Method Of Signal Recognition 7/12The Application of Neural Networks in Radar Signals Recognition - radiation source class - measure vector

8 Neural Network and Classic Method Of Signal Recognition 8/12The Application of Neural Networks in Radar Signals Recognition  the quantity of klass: L=10  the quantity of parametres: L=10  standard deviation:  The quantity of realizations for each class: n=100 NEURAL NETWORK: - THREE-LAYER PERCEPTRON - 10 SUBNETWORKS CLASSIC METHOD: - MINIMUM DISTANCE CLASSIFIER

9 Number Of Correct Classifications Stand.Dev. σ =0,2 σ =0,3 σ =0,6 SIGNAL CLASS S.S.N.M. M-O.S.S.N.M. M-O. S.S.N.M. M-O. 110009881000790911158 21000985 771823131 310009881000799942138 410009851000785974169 510009841000802914144 61000988994787870148 71000985999803883150 8100098410008031000145 910009891000794996120 1010009851000778977146 N.N. – Neural Network ST.R. – Minimum Distance Method 9/12The Application of Neural Networks in Radar Signals Recognition

10 Probability Of Correct Classification 10/12The Application of Neural Networks in Radar Signals Recognition  NEURAL NETWORK  CLASSIC METHOD

11 Summary  Use of neural networks instead of classic method for radar signals recognition is more effective  Modular network structure makes its development quick and easy  Application of the neural networks - promising 11/12The Application of Neural Networks in Radar Signals Recognition

12 12/12The Application of Neural Networks in Radar Signals Recognition


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