Radar Signal Detection In Non-Gaussian Noise Using RBF Neural Network

Radar Signal Detection In Non-Gaussian Noise Using RBF Neural Network

In this paper, we suggest a neural network signal detector using radial basis function (RBF) network. We employ this RBF Neural detector to detect the presence or absence of a known signal corrupted by different Gaussian, non-Gaussian and impulsive noise components. In case of non-Gaussian noise, experimental results show that RBF network signal detector has significant improvement in performan...

Use of Rbf Neural Network in Emg Signal Noise Removal

The bioelectric potentials associated with muscle activity constitute the electromyogram (EMG). EMG signal is used in biomedical applications to detect abnormal muscle electrical activity that occur in many diseases and conditions like muscular dystrophy, inflammation of muscles, pinched nerves, peripheral nerve damages, amyotrophic lateral sclerosis, disc herniation, myasthenia gravis and othe...

adaptive radar signal detection in gaussian clutter with autoregressive model using kalman fillter

in this paper, we deal with the problem of adaptive coherent signal detection in gaussian interference (clutter plus noise) for surveillance pulse radars. some of the adaptive radar detectors exploit the ar model for clutter. most of these detectors have been obtained using the glr test. this test relies on the maximum likelihood estimation whose accuracy depends on the number of data. whereas,...

Random signal detection in correlated non-Gaussian noise

Le problème de la détection d’un signal aléatoire noyé dans un bruit additif non gaussien modélisé par un processus sphériquement invariant est adressé. Une structure asymptotiquement optimale pour la détection d’un signal gaussien est synthétisée. Les performances de cette structure de détection sont obtenues par des simulations de Monte Carlo. De plus, des comparaisons sont effectuées avec le...

Signal Detection and Modulation Classification in Non-Gaussian Noise Environments