Non-linear Adaptive Prediction of Speech with a Pipelined Recurrent Neural Network and Advanced Learning Algorithms

نویسندگان

  • Danilo Mandic
  • Jens Baltersee
  • Jonathon Chambers
چکیده

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

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Non-linear Adaptive Prediction of Speech with a Pipelined Recurrent Neural Network and a Linearised Recursive Least Squares Algorithm

A novel linearised Recursive Least Squares (LRLS) learning algorithm is presented for an adaptive non-linear forward predictor based on a Pipelined Recurrent Neural Network (PRNN). Simulation studies with speech signals show that the non-linear predictor does not perform satisfactorily when the previously proposed stochastic gradient (SG) algorithm is used. However, significantly improved resul...

متن کامل

Nonlinear adaptive prediction of speech with a pipelined recurrent neural network

New learning algorithms for an adaptive nonlinear forward predictor that is based on a pipelined recurrent neural network (PRNN) are presented. A computationally efficient gradient descent (GD) learning algorithm, together with a novel extended recursive least squares (ERLS) learning algorithm, are proposed. Simulation studies based on three speech signals that have been made public and are ava...

متن کامل

Reinforcement Learning in Neural Networks: A Survey

In recent years, researches on reinforcement learning (RL) have focused on bridging the gap between adaptive optimal control and bio-inspired learning techniques. Neural network reinforcement learning (NNRL) is among the most popular algorithms in the RL framework. The advantage of using neural networks enables the RL to search for optimal policies more efficiently in several real-life applicat...

متن کامل

Reinforcement Learning in Neural Networks: A Survey

In recent years, researches on reinforcement learning (RL) have focused on bridging the gap between adaptive optimal control and bio-inspired learning techniques. Neural network reinforcement learning (NNRL) is among the most popular algorithms in the RL framework. The advantage of using neural networks enables the RL to search for optimal policies more efficiently in several real-life applicat...

متن کامل

A Comparison between Recurrent Neural Architectures for Real-time Nonlinear Prediction of Speech Signals

This paper presents a comparative study on the performance of recurrent neural networks trained in real-time to predict the next sample in a speech signal. The comparison is basically done versus linear predictors, and a pipelined recurrent neural network which has been proposed for this task. Results confirm those of previous works where limitations to deal with numeric time series were detect...

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

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

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2007