Complexity in time-delay networks of multiple interacting neural groups
نویسندگان
چکیده
منابع مشابه
Decentralized Adaptive Control of Large-Scale Non-affine Nonlinear Time-Delay Systems Using Neural Networks
In this paper, a decentralized adaptive neural controller is proposed for a class of large-scale nonlinear systems with unknown nonlinear, non-affine subsystems and unknown nonlinear time-delay interconnections. The stability of the closed loop system is guaranteed through Lyapunov-Krasovskii stability analysis. Simulation results are provided to show the effectiveness of the proposed approache...
متن کاملPhoneme recognition using time-delay neural networks
In this paper we present a Time-Delay Neural Network (TDNN) approach to phoneme recognition which is characterized by two important properties. 1) Using a 3 layer arrangement of simple computing units, a hierarchy can be constructed that allows for the formation of arbitrary nonlinear decision surfaces. The TDNN learns these decision surfaces automatically using error backpropagation 111. 2) Th...
متن کاملTime-delay Neural Networks for Control
This paper presents results regarding the application of Time-Delay Neural Networks (TDNNs), up to now mainly used in speech recognition, for control tasks. A set of examples taken from a model-based robot controller is used to validate the suitability of the TDNN and to show its superiority to standard multilayer perceptrons. Afterwards, a new algorithm is presented that shows how the inherent...
متن کاملBearing estimation with time-delay neural networks
In this paper we present a neuromimetic approach to bearing estimation issue. The proposed method is based on time-delay neural networks. This kind of network is well suited to take into account constraints encountered in signal processing: it deals with the dynamic nature of signal and discovers acoustic and temporal features. According to the propagation model of plane waves, the network has ...
متن کاملFast Complex Valued Time Delay Neural Networks
Here, a new idea to speed up the operation of complex valued time delay neural networks is presented. The whole data are collected together in a long vector and then tested as a one input pattern. The proposed fast complex valued time delay neural networks uses cross correlation in the frequency domain between the tested data and the input weights of neural networks. It is proved mathematically...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Electronic Research Archive
سال: 2021
ISSN: 2688-1594
DOI: 10.3934/era.2021022