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Application of ACO-LMBP Hybrid Neural Network Algorithm in Image Denoising

机译:ACO-LMBP混合神经网络算法在图像去噪中的应用

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In order to overcome the disadvantages of poor global search ability, slow convergence speed and easy to fall into local minimum in the traditional BP neural network in image denoising, a hybrid ACO-LMBP neural network image denoising algorithm based on ant colony algorithm and LMBP algorithm is proposed. ACO-LMBP hybrid neural network algorithm has both the high speed of LMBP algorithm and the global nature of ACO algorithm. It can improve the problems of BP algorithm model very well. By comparing with the image denoising effect of Wiener filtering, BP, LMBP and PSO-LMBP model, the denoising model using the ACO-LMBP neural network algorithm has better denoising effect.
机译:为了克服全球搜索能力差,收敛速度较差,易于陷入局部BP神经网络中的局部最小值,其在图像去噪中,一种基于蚁群算法和LMBP算法的混合ACO-LMBP神经网络去噪算法提出。 ACO-LMBP混合神经网络算法具有LMBP算法的高速和ACO算法的全局性质。它可以提高BP算法模型的问题。通过比较Wiener滤波,BP,LMBP和PSO-LMBP模型的图像去噪效果,使用ACO-LMBP神经网络算法的去噪模型具有更好的去噪效果。

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