Neural Networks and Nonlinear Adaptive Filtering: Unifying Concepts and New Algorithms

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Neural Networks and Nonlinear Adaptive Filtering: Unifying Concepts and New Algorithms

The paper proposes a general framework which encompasses the training of neural networks and the adaptation of filters. We show that neural networks can be considered as general non-linear filters which can be trained adaptively, i. e. which can undergo continual training with a possibly infinite number of time-ordered examples. We introduce the canonical form of a neural network. This canonica...

متن کامل

Adaptive Information Filtering concepts and algorithms

Adaptive information filtering is concerned with filtering information streams in dynamic (changing) environments. The changes may occur both on the transmission side — the nature of the streams can change — and on the reception side — the interests of the user (or group of users) can change. While information filtering and information retrieval have a lot in common, this dissertation’s primary...

متن کامل

Adaptive Leader-Following and Leaderless Consensus of a Class of Nonlinear Systems Using Neural Networks

This paper deals with leader-following and leaderless consensus problems of high-order multi-input/multi-output (MIMO) multi-agent systems with unknown nonlinear dynamics in the presence of uncertain external disturbances. The agents may have different dynamics and communicate together under a directed graph. A distributed adaptive method is designed for both cases. The structures of the contro...

متن کامل

Unifying Bilateral Filtering and Adversarial Training for Robust Neural Networks

Recent analysis of deep neural networks has revealed their vulnerability to carefully structured adversarial examples. Many effective algorithms exist to craft these adversarial examples, but performant defenses seem to be far away. In this work, we attempt to combine denoising and robust optimization methods into a unified defense which we found to not only work extremely well, but also makes ...

متن کامل

Modelling and Adaptive Filtering of Nonlinear Systems Using Neural Network

For some classes of nonlinear systems or time series, an operating point dependent ARMA model can be used to represent the system. In this paper we use the neural networks to identify such a model which can then be converted to its equivalent state-space representation. Using this state-space form, a Kalman lter can be applied to estimate the state, and a simulated example is given.

متن کامل

ذخیره 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: Neural Computation

سال: 1993

ISSN: 0899-7667,1530-888X

DOI: 10.1162/neco.1993.5.2.165