A neural net capable of restoring continuous level library vectors from memory is considered. As with Hopfield's neural net content addressable memory, the vectors in the memory library are used to program the neural interconnects. Given a portion of one of the library vectors, the net extrapolates the remainder. Sufficient conditions for convergence are stated. Effects of processor inexactitud...

Gliomas are the largest prevalent and destructive of brain tumors have crucial parts for diagnosing treating MRI during segmentation using computerized methods. Recently, U-Net architecture has achieved impressive tumor segmentation, but this role remains challenging due to differing severity appearance gliomas. Therefore, we proposed a novel encoder–decoder called Multi Inception Residual Atte...

In this paper, we explore the application of Recursive Neural Networks on the sentiment analysis task with tweets. Tweets, being a form of communication that has been largely infused with symbols and short-hands, are especially challenging as a sentiment analysis task. In this project, we experiment with different genres of neural net and analyze how models suit the data set in which the nature...

Abstract In this article we introduce the p -adic cellular neural networks which are mathematical generalizations of classical (CNNs) introduced by Chua and Yang. The new have infinitely many cells organized hierarchically in rooted trees, also they hidden layers. Intuitively, CNNs occur as limits large hierarchical discrete CNNs. More precisely, can be very well approximated Mathematically spe...

This paper presents a survey of neural network controllers for AUVs. A direct adaptive neural net controller incorporating integral action was designed for the heave motion of the ODIN underwater vehicle. The neural net controller is trained on-line by parallel recursive error prediction method and the critic equation. The influence of the various design parameters of the neural net controller ...

<span lang="EN-US">The next generation of wireless cellular communication networks must be energy efficient, extremely reliable, and have low latency, leading to the necessity using algorithms based on deep neural (DNN) which better bit error rate (BER) or symbol (SER) performance than traditional complex multi-antenna multi-input multi-output (MIMO) detectors. This paper examines iterati...