B超乳腺图像小波阈值去噪方法研究

小波阈值去噪是小波阈去噪的主要方法之一,文中对B超乳腺图像进行噪声分析,在小波分解的基础上,将不同的阈值函数和不同方式选取的阈值相结合,分析其原理和方法,并利用Matlab实现,给出实验结果对比,为医学B超图像去噪提供参考依据。     

基于对比度调制法对条纹管激光雷达距离像的去噪方法

激光雷达的距离像是雷达成像系统区别于其他的成像系统（如红外成像系统、可见光成像系统）所特有的信息,它是对目标精确识别、打击的基础。如何对距离像去噪直接决定了下一步目标定位、识别的精确性。针对雷达距离像的特点,提出了一种基于对比度调制方法对条纹管激光雷达的距离像去噪方法,通过提取距离像噪声的对比度信息,用其调制未经过去噪的距离像,从而得到距离像中的噪声图像,最后用未经过处理的距离像减去噪声图像,得到图像即为去噪后距离像。研究表明该方法去噪效果明显,在去噪的同时很好地保持了距离像的边缘信息,去噪后图像的信噪比明显提高,距离像的属性也没有改变,这是其他方法对距离像去噪所不具有的优点。     

Daubechies小波在东北某盆地资料分析中的应用

重、磁场异常分离技术是进行重、磁异常解释的关键。通过研究Daubechies小波原理,并应用于东北某盆地资料分析中,分别对原始重、磁实际异常数据进行不同阶次的划分实验,利用对数功率谱估算场源深度,分解出的场源深度基本对应盆地基底深度,说明Daubechies小波在重、磁异常多尺度分解中具有良好效果。     

Analysis of prediction performance in wavelet minimum complexity echo state network

Echo state network （ESN） has become one of the most popular recurrent neural networks （RNN） for its good prediction performance of non-linear time series and simple training process. But several problems still prevent ESN from becoming a widely used tool. The most prominent problem is its high complexity with lots of random parameters. Aiming at this problem, a minimum complexity ESN model （MCESN） was proposed. In this paper, we proposed a new wavelet minimum complexity ESN model （WMCESN） to improve the prediction accuracy and increase the practical applicability. Our new model inherits the characters of minimum complexity ESN model using the fixed parameters and simple circle topology. We injected wavelet neurons to replace the original neurons in internal reservoir and designed a wavelet parameter matrix to reduce the computing time. By using different datasets, our new model performed better than the minimum complexity ESN model with normal neurons, but only utilized tiny time cost. We also used our own packets of transmission control protocol （TCP） and user datagram protocol （UDP） dataset to prove that our model can deal with the data packet bit prediction problem well.     

Wavelet domain denoising method based on multistage median filtering

There are two main problems in the threshold denoising method based on wavelet transform. One is the difficulty of threshold selection, and the other is the inconsistence of the dip and curved events in the low signal-to-noise ratio (SNR) seismic data after denoising. In image denoising, multistage median filtering can preserve the details of the signal. So we proposed a denoising algorithm in wavelet transform domain based on multistage median filtering. Using this method the flat region and the edge region are differentiated by the difference between the maximum mid-value and the minimum mid-value, which preserves the details, thus improves the denoising effect. The simulation data and the real data processing results reveal that this method has stronger ability in separating signal from noise than that of the threshold denoising method.     

基于光纤光栅传感技术的复合材料损伤检测

随着科学技术的不断进步和发展,越来越多的新型复合材料构件在工业制造过程中被采用,然而复合材料在服役过程中一旦损坏将造成巨大的损失,因此对复合材料的结构健康检测显得十分重要。将布拉格光纤光栅（FBG）传感技术应用于玻璃纤维复合材料薄板检测,采用主动冲击的方式在玻璃纤维复合材料板上激励声波,采集损伤前后的冲击响应信号,研究基于小波包能量谱的冲击响应的损伤识别。通过小波包分解,得到损伤前后的小波能量谱变化比直方图,比较图中各阶小波包能量比,能够实现复合材料的损伤识别。     

基于DWT变换的语音信息隐藏技术研究

本文基于小波域低频系数模数运算,提出了一种将数字水印隐藏在公开语音中的语音信息隐藏算法.我们将降维处理后的二值水印嵌入到音频信号的低频小波系数中,然后对低频小波系数进行模数运算,并根据运算结果对音频系数值进行修改,嵌入水印.提取时按照同样方法,将音频信号小波分解得到的低频系数进行模数运算,升维后得到提取水印.仿真实验表明,该水印算法在噪声、滤波、重量化和重采样等攻击时具有较好的鲁棒性.     

Distributed Compressive Video Sensing with Adaptive Measurements Based on Structural Similarity

This paper presents a Distributed compressive video sensing scheme with Adaptive measurements （DCVS-AM）. In this approach, the key frame in each Group of pictures （GOP） is coded by Compressive sensing （CS） with a fixed measurement rate; whereas other frames in the same GOP are compressed by an adaptive random projection in two stages, yielding the Adaptive compressive sensing （ACS） frames. The first stage uses a small and fixed measurement rate and recovers a coarse version. In the second stage, each coarse-version ACS-frame together with its proceeding and following key frames will go through a joint analysis at the decoder side and the analysis result - Structural similarity （SSIM） that is based on a motion-guided interpolation and calculated in a multilevel discrete wavelet transform domain - is sent back to the encoder side to facilitate a re-sampling of the ACS-frame with an adaptive measurement rate. Experimental results show that our proposed DCVS-AM consistently outperforms the state-of-the-art DCVS with a fixed measurement.     

Exact solutions of multi-term fractional diffusion-wave equations with Robin type boundary conditions

General exact solutions in terms of wavelet expansion are obtained for multi- term time-fractional diffusion-wave equations with Robin type boundary conditions. By proposing a new method of integral transform for solving boundary value problems, such fractional partial differential equations are converted into time-fractional ordinary differ- ential equations, which are further reduced to algebraic equations by using the Laplace transform. Then, with a wavelet-based exact formula of Laplace inversion, the resulting exact solutions in the Laplace transform domain are reversed to the time-space domain. Three examples of wave-diffusion problems are given to validate the proposed analytical method.     

一种算子自定义小波薄板单元及应用

提出了基于提升方案的自适应算子自定义小波有限元法,构造了一种新的算子自定义小波薄板单元。建立二维Hermite型有限元多分辨空间和两尺度关系,并由广义变分原理推导薄板结构关于尺度函数和小波函数的内积关系式,即算子。为满足算子正交性,提出基于提升方案的算子自定义小波单元的构造方法,其优点在于可根据问题的需要来设计具有期望特性的小波基。提出基于两尺度误差的自适应算子自定义小波有限元方法,通过向大于误差阈值的局域添加算子自定义小波,实现薄板结构问题的高效求解。算子自定义小波有限元法节省了重新划分网格或提高插值函数的阶次所带来的大量有限元前处理时间,并且实现薄板问题的高效解耦运算。