The properties of the wavelet networks are analyzed. According to the approximation ability of wavelet networks, the nonlinear static system and the nonlinear dynamic system can be identified.
分析了小波网络的性能，利用小波网络的非线性函数逼近能力，对非线性静态系统和非线性动态系统进行辨识。
Based on the learning characteristic of neural network and the function approximation ability of the wavelet, a new self tuning control algorithm is presented.
依据小波的非线性逼近能力和神经网络的自学习特性，提出了一种基于小波神经网络模型的自校正控制算法。
The algorithm improves the EZW algorithm through inducting fast successive approximation quantization and effective treatment of marginal subband of wavelet transform.
该方法通过引入快速逐次逼近量化和对小波变换边缘子带的特殊处理，对EZW算法进行了改进。
An efficient scheme for video coding is presented which utilizes progressive fractal coding, called wavelet-based fractal approximation (WBFA), and motion compensation (MC).
利用改进的分形编码提出了一种有效的视频编码方法，称作基于小波分形逼近(WBFA)，和运动补偿(MC)。
Then, it approximates the environment map in the same wavelet basis by keeping only the largest terms to get a non-linear approximation of the environment-map.
然后用相同的小波基对给定的环境光做小波变换，只保留其中绝对值较大的系数，从而得到环境光的非线性逼近。
Then, watershed segmentation of the approximation image is computed, and the inverse wavelet transform is used to project this original segmentation up to the higher resolutions.
对近似图像进行分水岭分割，并且用小波逆变换把原始分割结果逐步映射回更高的分辨率层。
The approximation coefficient from wavelet decomposition includes much information relating with device reliability and is more sensitive to the change of device performance.
小波分解后的概貌信息，具有更多的可靠性细节信息，对器件性能的改变更敏感。
The discrete wavelet transform decomposes a discrete time signal into an approximation sequence and a detail sequence at each level of resolution.
离散子波变换将离散时间信号分解为一系列分辨率下的离散逼近和离散细节。紧支的正交规范子波与完全重建正交镜象滤波器组相对应。
The wavelet neural network, which has good approximation and generalization performance in nonlinear modeling, is used to predict the final settlements of soft ground in expressway.
利用小波神经网络在非线性建模中的收敛迅速等优越性 ，提出利用小波神经网络预测高速公路软土地基的最终沉降量的方法。
The wavelet neural network, which has good approximation and generalization performance in nonlinear modeling, is used to predict the final settlements of soft ground in expressway.
利用小波神经网络在非线性建模中的收敛迅速等优越性 ，提出利用小波神经网络预测高速公路软土地基的最终沉降量的方法。
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