Deep Neural Network-Based Interrupted Sampling Deceptive Jamming Countermeasure Method

An Adaptive Transmitting Scheme for Interrupted Sampling Repeater Jamming Suppression

The interrupted sampling repeater jamming (ISRJ) based on a digital radio frequency memory (DRFM) device is a new type of coherent jamming. This kind of jamming usually occurs as main-lobe jamming and has the advantages of low power requirements and easy parameter adjustment, posing a serious threat to the modern radar systems. In order to suppress the ISRJ, this paper proposes an adaptive tran...

Deep Neural Network-Based Method for Economic Dispatch in Microgrid

Image Retrieval Method for Deep Neural Network

Because of the large data in the image database, the key problem of the retrieval algorithm is to retrieve the required image in the short time. Aiming at this problem, this article given a self-learning deep belief neural network method, and through building layers, input, output, and self-learning algorithm in network architecture to get global algorithm for image retrieval. The accuracy and ...

A conjugate gradient based method for Decision Neural Network training

Decision Neural Network is a new approach for solving multi-objective decision-making problems based on artificial neural networks. Using inaccurate evaluation data, network training has improved and the number of educational data sets has decreased. The available training method is based on the gradient decent method (BP). One of its limitations is related to its convergence speed. Therefore,...

Deceptive Opinion Spam Detection Using Neural Network

Deceptive opinion spam detection has attracted significant attention from both business and research communities. Existing approaches are based on manual discrete features, which can capture linguistic and psychological cues. However, such features fail to encode the semantic meaning of a document from the discourse perspective, which limits the performance. In this paper, we empirically explor...