Four distributed feedback laser array integrated with multimode-interference and semiconductor optical amplifier

Monolithic integration of four 1.55-μm-range InGaAsP/InP distributed feedback (DFB) lasers using varied ridge width with a 4×1-multimode-interference (MMI) optical combiner and a semiconductor optical amplifier (SOA) is demonstrated. The average output power and the threshold current are 1.8 mW and 35 mA, respectively, when the injection current of the SOA is 100 mA, with a side mode suppression ratio (SMSR) exceeding 40 dB. The four channels have a 1-nm average channel spacing and can operate separately or simultaneously.     

Stochastic resonance in multi-scale bistable array

This Letter explores a new mechanism of stochastic resonance (SR) that is induced by the multi-scale noise decomposed from the input signal, which is promising in signal detection and processing under heavy background noise. The input signal is firstly decomposed to multi-scale signals by orthogonal wavelet transform. Then, the approximate signal, which contains the driving signal, is processed by an uncoupled parallel bistable array with the detailed signal of each scale as the internal noise. At last, a SR mechanism combining the effects of colored noise and array SR is proposed. The simulation results show that a high quality output signal can be obtained by the new mechanism. The proposed model is more adaptive to input signal with high noise intensity than single bistable SR system, which can be seen from the signal-to-noise ratio curves and average noise intensity curves.     

Aliasing Error of Sampling Series in Wavelet Subspaces

Alising error arises whenever a sampling formula, valid for a prescribed space, is applied to a function in a bigger space. In this work, we estimate the aliasing error of classic and average sampling expansions in wavelet subspaces of a multiresolution analysis.     

Wavelet-modified fringe-adjusted joint transform correlator

In this paper, we implement a wavelet-modified fringe-adjusted joint transform correlator (JTC) for real-time target recognition applications. In real-time situation the input scene is captured using a charge-coupled device (CCD) camera. The obtained joint power spectrum is multiplied by a pre-synthesized fringe-adjusted filter and the resultant function is processed with an appropriately scaled wavelet filter. Three performance measure parameters: correlation peak intensity, peak-to-sidelobe ratio, and signal-to-clutter ratio have been calculated for fringe-adjusted joint transform correlator (FJTC) and wavelet-modified fringe-adjusted joint transform correlator (WFJTC). The WFJTC has been found to yield better results in comparison to conventional FJTC. To suppress the undesired strong dc, the resultant function is differentiated. Differential processing wavelet-modified fringe-adjusted joint power spectrum removes the zero-order spectra and hence improves the detection efficiency. To focus the correlation terms in different planes in order to capture one of the desired autocorrelation peaks and discard the strong dc and another autocorrelation peak, chirp-encoding technique has also been applied. Targets with Gaussian and speckle noise have also been used to check the correlation outputs. Computer simulation and experimental results are presented.     

Intensity analysis methods for transient signals

Conventionally, the Fourier transform is applied for sound intensity analysis of stationary signals, but this method can be applied for analyzing non-stationary transient signals. Instead of the Fourier transform analysis, instantaneous spectrum analysis methods such as the Wigner-Ville distribution and the wavelet transform are proposed. By using the mathematical example as a transient signal, advantages and disadvantages of these methods including the short-time Fourier transform are compared. From calculation results, it is considered that the STFT method is the most suitable for the accurate measurement of sound intensity levels, but the WT method is also recommended from its higher resolution of transient signals.     

Application of multifractal wavelet analysis to spontaneous fermentation processes

An algorithm is presented here to get more detailed information, of mixed-culture type, based exclusively on the biomass concentration data for fermentation processes. The analysis is performed with only the on-line measurements of the redox potential being available. It is a two-step procedure which includes an Artificial Neural Network (ANN) that relates the redox potential to the biomass concentrations in the first step. Next, a multifractal wavelet analysis is performed using the biomass estimates of the process. In this context, our results show that the redox potential is a valuable indicator of microorganism metabolic activity during the spontaneous fermentation. In this paper, the detailed design of the multifractal wavelet analysis is presented, as well as its direct experimental application at the laboratory level.     

基于最小各向同性小波滤波的图像清晰度识别

提出了基于最小各向同性小波滤波的图像清晰度识别方法,对二维最小各向同性小波滤波提取图像特征进行了研究.直接将原始图像通过带通小波滤波器G0获得图像边缘信息,结合图像能量分析,建立了基于小波滤波的图像清晰度评价函数.利用构建的显微镜自动对焦实验平台,比较分析了基于小波滤波和拉普拉斯的评价方法.实验结果表明,采用基于各向同性小波滤波的自动对焦算法有更好的综合自动对焦性能.     

光学移相干涉仪抗振系统的鲁棒μ控制器设计

将结构奇异值μ综合鲁棒控制技术应用于主动抗振控制系统中,并用于解决光学移相干涉仪抗振系统的不确定性问题.采用小波分析方法将随机振动信号进行时频分析后得到低频全局信息,随后运用μ综合D-K迭代法设计鲁棒μ控制器对低频振动进行抑制.该方法克服了由模型自身和外部干扰所引起的不确定性,使得控制系统能够有效地抑制抗振模型的不确定性和外部振动的干扰,同时也具有很高的控制准确度和灵敏度.仿真结果表明,该方法使光学移相干涉仪在外部振动的干扰下具有较好的鲁棒稳定性和控制准确度,同时也能较好地抑制低频振动.     

Intertwining wavelets or multiresolution analysis on graphs through random forests

We propose a new method for performing multiscale analysis of functions defined on the vertices of a finite connected weighted graph. Our approach relies on a random spanning forest to downsample the set of vertices, and on approximate solutions of Markov intertwining relation to provide a subgraph structure and a filter bank leading to a wavelet basis of the set of functions. Our construction involves two parameters q and $q^{\prime }$. The first one controls the mean number of kept vertices in the downsampling, while the second one is a tuning parameter between space localization and frequency localization. We provide an explicit reconstruction formula, bounds on the reconstruction operator norm and on the error in the intertwining relation, and a Jackson-like inequality. These bounds lead to recommend a way to choose the parameters q and $q^{\prime }$. We illustrate the method by numerical experiments.