This paper is to provide an alternative approach for the equiripple design of FIR filters by using a Hopfield Neural Network (HNN). The proposed approach establishes the error function between the amplitude response of the desired FIR filter and the designed one as a Lyapunov energy function to find the HNN parameters. Using the framework of HNN, the optimal filter coefficients can be obtained ...

To integrate the hierarchy structure of discrimination between all HMM states for Chinese Initials and Finals, we constructed in this paper Hierarchical Neural Networks (HNN), which differ from Jordan's HME in such extensions as more complex parameterization for gate and/or expert and dimension-reduced expert network. With these extensions, we can reuse those pre-trained simple node networks in...

A Hopfield Neural Network (HNN) with a new weight update rule can be treated as a second order Estimation of Distribution Algorithm (EDA) or Fitness Function Model (FFM) for solving optimisation problems. The HNN models promising solutions and has a capacity for storing a certain number of local optima as low energy attractors. Solutions are generated by sampling the patterns stored in the attr...

The Hopfield neural network (HNN) is one major neural network (NN) for solving optimization or mathematical programming (MP) problems. The major advantage of HNN is in its structure can be realized on an electronic circuit, possibly on a VLSI (very large-scale integration) circuit, for an on-line solver with a parallel-distributed process. The structure of HNN utilizes three common methods, pen...

In this paper, we presented the 4.0, 2.7, 2.5 mm, width, length, height size biomimetics micro robot system which was inspired by insects. The micro robot system was made from silicon wafer fabricated by micro electro mechanical systems (MEMS) technology. The mechanical system of the robot was equipped with small size rotary type actuators, link mechanisms and six legs to realize the ins...

This work presents a new solution to overcome the obstacle of using Hopfield Neural Network (HNN) with high level images than binary images. While HNN deals with bipolar system for direct input data, still it is not useful for graylevel or color images. Supposing for 8-bit gray-level image consists of 8-layers of bitplanes can be represented as bipolar data. Hence, it is possible to express eac...

Image classification was performed using Gabor wavelet filters for image feature extraction, self-organising maps (SOM) for dimensional reduction of Gabor wavelet filters, and forward (FNN), Hermite (HNN) and Laguerre (LNN) neural networks to classify real and artificial fingerprint images from optical coherence tomography (OCT). Use of a SOM after Gabor edge detection of OCT images of fingerpr...

A group is called HNN-free if it has no subgroups that are nontrivial HNN-extensions. 23 We prove that finitely generated HNN-free implies virtually polycyclic for a large class of groups. We also consider finitely generated groups with no free subsemigroups of rank 2 25 and show that in many situations such groups are virtually nilpotent. Finally, as an application of our results, we determine...