three_machines_nine_buses0

《无线通信与原理应用》中QPSK编码的误码率曲线绘制的代码，简洁易懂。有注释，方便修改。("Wireless communications and Principle" in the QPSK coded BER curve drawing code, concise and easy to understand. Notes, easy to modify.)

小波分析、局部放电试验所采集的信号中往往混有白噪声、周期干扰信号去除。此处采用常用db系列小波中的db6小波进行9尺度的多分辨分解后，根据白噪声能量特性，估算各尺度的阈值大小，采用硬值进行处理，后进行重构。(Wavelet Analysis、Signal acquired partial discharge test is often mixed with white noise, periodic interference signal removal. Db series wavelet commonly used here in db6 9 scale wavelet multi-resolution decomposition, according to the energy characteristics of white noise, the estimated size of each scale thresholds, hard-value processing, after reconstruction.)

Format Linked List for sparse Matrix

kalman跟踪滤波程序目标运动状况kalman-filterl滤波result输出结果(alman filtering programs target movement condition filterl kalman filter- much output)

an api used for diffrent things

在基于Mean-Shift的目标跟踪算法中，尺度自适应机制是算法研究的一个重要方向。一种典型的方法采 用Lindeberg的尺度空间理论以获取目标尺度信息。但现有算法中将尺度由2．D矢量压缩为1一D量，未能精细地 刻画目标仿射变换时的尺度变化，从而限制了算法的适用范围。为此，该文将尺度维1．D滤波推广至2一D，构造得 到了相应的垂D尺度空间，并利用窄间维和尺度维的Mean-Shift交替迭代，实现了同时在空间位置和尺度方向对 目标的有效跟踪，提高了算法在目标尺度变化时的自适应性，并扩大了算法的适用范围。 关键(Scale adaptive mechanism in the target tracking algorithm based on Mean-Shift algorithm is an important direction of research. A typical method using Lindeberg' s scale space theory to obtain the target scale. However, the existing algorithms will scale from 2. D vector compression for 1-D volume, not fine to portray the target affine transformation of scale changes, thus limiting the scope of application of the algorithm. To this end, the paper will scale dimension. D filter to the 2-D structure has been the vertical D scale space and the use of narrow inter-dimension and scale dimension of the Mean-Shift alternating iteration, effective tracking of the target position in space and scale direction to improve the self-adaptive algorithm when the target scale changes, and to expand the scope of application of the algorithm. Key)

The model used for creating the reference voltage is shown in Fig. 4. First, photovoltaic output current (Ipv) and output voltage (Vpv) are passed through a first order low pass filter with a magnitude of G = 1 and a time constant of T = 0.01 seconds in order to filter out the high frequency components or harmonics from these signals as shown in Fig. 5 and Fig. 6. The filtered current and voltage signals (Ipv_F and Vpv_F) are then fed into the MPPT control block that uses the Incremental Conductance Tracking Algorithm. An algorithm that is based on the fact the slope of the PV array power curve shown in Fig. 7 is zero at the Maximum Power Point (MPP), positive on the left of the MPP, and negative on the right. The MPP can thus be tracked by comparing the instantaneous conductance (I/V) to the incremental conductance (∆ I/∆ V) [11] as in (1):

system sade for solotion

已知三基准点和原点，通过未知点、基准点与原点距离，未知点与基准点距离，求未知点坐标(Known three reference points and the origin, through unknown point, the reference point and the origin of the distance from the unknown point and the reference point, find the coordinates of the unknown point)

single server queue program