噪声主动控制的入门书籍 澳大利亚汉森 部分目录： CHAPTER ONE. A LITTLE HISTORY ........................................................... 1 1.1 INTRODUCTION ...................................................................................... 1 1.2 EARLY HISTORY ........
Recurrent Neural Networks: Design and Applications Lakhmi C. Jain Larry Medsker With existent uses ranging from motion detection to music synthesis to financial forecasting, recurrent neural networks have generated widespread attention. The tremendo
Recently, a new learning algorithm for the feedforward neural network named the extreme learning machine (ELM) which can give better performance than traditional tuning-based learning methods for feedforward neural networks in terms of generalizatio
The particle swarm optimization algorithm was showed to converge rapidly during the initial stages of a global search, but around global optimum, the search process will become very slow. On the contrary, the gradient descending method can achieve f
In this paper, a new design and tuning procedure for a PID plus feedforward controller is proposed. It consists of determining a feedforward signal in order to achieve a predefined process output transition time assuming a first order plus dead time
Abstract—This work discusses reference trajectory relevant model based feedforward design. For motion systems which contain at least one rigid body mode and which are subject to reference trajectories with mostly low frequency energy, the proposed f
Source Code: A Feedforward Architecture Accounts for Rapid Categorization，This code provides a framework for reproducing the main experimental result described in: T. Serre, A. Oliva & T. Poggio, "A feedforward architecture accounts for rapid catego
