An algorithm for multi-input multi-output (MIMO) adaptive filtering is introduced that distributes the adaptive computation over a set of linearly connected computational modules. Each module has an input and an output and transmits data to and receives data from its nearest neighbor. A gradient-based algorithm for adapting the parameters in each module to minimize the global mean-squared error...

the use of neural networks methodology is not as common in the investigation and pre-diction noise as statistical analysis. the application of artificial neural networks for pre-diction of power tiller noise is set out in the present paper. the sound pressure signals for noise analysis were obtained in a field experiment using a 13-hp power tiller. during measurement and recording of the sound ...

suspended particles have deleterious effects on human health and one of the reasons why tehran is effected is its geographically location of air pollution. one of the most important ways to reduce air pollution is to predict the concentration of pollutants. this paper proposed a hybrid method to predict the air pollution in tehran based on particulate matter less than 10 microns (pm10), and the...

Owing to the heterogeneity of software and hardware in different types mobile terminals, received signal strength indication (RSSI) from same Wi-Fi access point (AP) varies indoor environments, which can affect positioning accuracy fingerprint methods. To solve this problem consider nonlinear characteristics propagation attenuation, we propose a whale optimisation algorithm-back-propagation neu...

In this study, error compensation technology was proposed to reduce thermal errors of a gear hobbing machine, and one experiment was carried out to verify the compensation effect. Different thermal sources were used as modeling variables, and a prediction model of thermal errors was presented based on back propagation (BP) neural networks. In order to solve local minimum problem of BP neural ne...

This paper proposes a new sliding mode controller using neural networks. Multilayer neural networks with the error back-propagation learning algorithm are used to compensate for the system uncertainty in order to reduce the tracking error and control torque. The stability of the proposed control scheme is proved with the Lyapunov function method. Computer simulation shows that the control perfo...