Global dissipativity of high-order Hopfield bidirectional associative memory neural networks with mixed delays

Fixed/prescribed-time synchronization of BAM memristive neural networks with time-varying delays via convex analysis

The synchronization problem of bidirectional associative memory memristive neural networks (BAMMNNs) with time-varying delays plays an essential role in the implementation and application of neural networks. Firstly, under the framework of the Filippov's solution, the discontinuous parameters of the state-dependent switching are transformed by convex analysis method, which is different from most previous approaches. Secondly, based on Lyapunov function and some inequality techniques, several conditions for the fixed-time synchronization (FXTS) of the drive-response systems are obtained by designing special control strategies. Moreover, the settling time (ST) is estimated by the improved fixed-time stability lemma. Thirdly, the driven-response BAMMNNs are investigated to be synchronized within a prescribed time by designing new controllers based on the FXTS results, where ST is irrelevant to the initial values of BAMMNNs and the parameters of controllers. Finally, a numerical simulation is exhibited to verify the correctness of the conclusions.

Sports Video Athlete Detection Based on Associative Memory Neural Network

Aiming at the detection of athletes in sports videos, an automatic detection method based on AMNN is proposed. The background image from the image sequence is obtained, the moving area is extracted, and the color information of pixels to extract the green stadium from the background image is used. In order to improve the accuracy of athletes' detection, the texture similarity measurement method is used to eliminate the shadow in the movement area, the morphological method is used to eliminate the cracks in the area, and the noise outside the stadium is removed according to the stadium information. Combined with the images of nonathletes, a training set is constructed to train the NN classifier. For the input image frames, image pyramids of different scales are constructed by subsampling and the positions of several candidate athletes are detected by NN. The center of gravity of candidate athletes is calculated, a representative candidate athlete is obtained, and then, the final athlete position through a local search process is determined. Experiments show that the system can accurately detect the motion shape of moving targets, can process images in real time, and has good real-time performance.

Delayed fuzzy genetic regulatory networks: Novel results

In this manuscript, we studied a class of delayed Fuzzy Genetic Regulatory Networks (FGRNs) with Stepanov-like weighted pseudo almost automorphic coefficients. New criteria for the existence, uniqueness and global exponential stability of its weighted pseudo almost automorphic solution are established. Our approach is based on Banach fixed point theorem and novel analysis techniques. Moreover, a numerical example is given to illustrate the validity of the obtained results.