A Hybrid Differential Evolution Approach to Designing Deep Convolutional Neural Networks for Image Classification

Convolutional Neural Networks (CNNs) have demonstrated their superiority in image classification, and evolutionary computation (EC) methods have recently been surging to automatically design the architectures of CNNs to save the tedious work of manually designing CNNs. In this paper, a new hybrid differential evolution (DE) algorithm with a newly added crossover operator is proposed to evolve the architectures of CNNs of any lengths, which is named DECNN. There are three new ideas in the proposed DECNN method. Firstly, an existing effective encoding scheme is refined to cater for variable-length CNN architectures; Secondly, the new mutation and crossover operators are developed for variable-length DE to optimise the hyperparameters of CNNs; Finally, the new second crossover is introduced to evolve the depth of the CNN architectures. The proposed algorithm is tested on six widely-used benchmark datasets and the results are compared to 12 state-of-the-art methods, which shows the proposed method is vigorously competitive to the state-of-the-art algorithms. Furthermore, the proposed method is also compared with a method using particle swarm optimisation with a similar encoding strategy named IPPSO, and the proposed DECNN outperforms IPPSO in terms of the accuracy.Comment: Accepted by The Australasian Joint Conference on Artificial Intelligence 201

System Design by Constraint Adaptation and Differential Evolution

A simple optimization procedure for constraint based problems which works without an objective function is described. The absence of an objective function makes the problem formulation particularly simple. The new method lends itself to parallel computation and is well suited for tasks where a family of solutions is required, trade-off situations have to be dealt with or the design center has to be found. ________________________________________ 1) International Computer Science Institute, 1947 Center Street, Berkeley, CA 94704-1198, Suite 600, Fax: 510-643-7684. E-mail: [email protected]. On leave from Siemens AG, ZFE T SN 2, OttoHahn -Ring 6, D-81739 Muenchen, Germany. Fax: 01149-636-44577, Email: [email protected]. 2 1. Introduction The design of a technical system is usually associated with the process of properly choosing some system parameters such that the technical system meets its specifications. The parameter choosing process can also be regarded as an o..

On the Usage of Differential Evolution for Function Optimization

Abstract assumed unless otherwise stated. Basically, DE Differential Evolution (DE) has recently proven to be an efficient method for optimizing real-valued multi-modal objective functions. Besides its good convergence properties and suitability for parallelization, DE's main assets are its conceptual simplicity and ease of use. This paper describes several variants of DE and elaborates on the choice of DE's control parameters which corresponds to the application of fuzzy rules. Finally the design of a howling removal unit with DE is described to provide a real-world example for DE's applicability.

Differential Evolution design of an IIRfilter with requirements for magnitude and group delay

The task of designing an 18 parameter IIR-filter which has to meet tight specifications for both magnitude response and group delay is investigated. This problem must usually be tackeled by specialized design methods and requires an expert in digital signal processing for its solution. The usage of the general purpose minimization method Differential Evolution (DE), however, allows to perform the filter design with a minimum knowledge about digital filters

Echo Cancellation Techniques for Multimedia Applications - a Survey

The problem of acoustical echo in a headset-free full duplex communication environment is explained and the potential solutions are sketched. The different methods for acoustic echo cancellation (AEC) via adaptive filters are outlined and their suitability for a 16-bit fixed point implementation on a digital signal processor (DSP) is evaluated. The current prototype for the ICSI Acoustic Echo Canceller (IAEC) which uses an allpass-based subband adaptive approach is introduced and directions for future work are given. ________________________________________ 1) International Computer Science Institute, 1947 Center Street, Berkeley, CA 94704-1198, Suite 600, Fax: 510-643-7684. E-mail: [email protected]. On leave from Siemens AG, ZFE T SN 2, Otto-Hahn-Ring 6, D-81739 Muenchen, Germany. Fax: 01149-89-636-44577, E-mail: [email protected]. 2 1. Introduction The occurrence of echoes is a well known problem for long distance communication links and has been experienced in..

Differential Evolution- A simple

and efficient adaptive scheme for global optimization over continuous space