Identification of Tones with Noises by Artificial Intelligence
Ivelina Stefanova Balabanova, Stela Savova Kostadinova, Valentina Ilieva Markova, Georgi Georgiev · 2020
The paper presents the results of the application of artificial backpropagation neural networks in identification of signal frequency tones with different RMS noise level. The Levenberg-Marquardt (LM) and Scaled Conjugate Gradient (SCG) training algorithms were applied in the processes of neural synthesis. Three-layer with 35 hidden neurons and four-layer architectures with 22 in the first and 11 neurons in the second hidden layer in hyperbolic tangent transfer functions with accuracies 96.00% and 98.00% in LM were selected. For SCG with softmax output activation function a neural network with the best accuracy 94.3% in 29 hidden neurons was synthesized.