ASSINGMENTB_RafalMajorczyk_-Sharp8

This source code simulates UWB based wireless Communication system which transmits color image over wireless medium. Modulation type: Pulse position modulation Pulse: second derivative of a Gaussian pulse Channel: AWGN Image: lib.jpg

关于LDPC编码的一些相关英文资料或者论文及有关资料(LDPC)

有关于S函数的，滑模变结构例程3,内涵simulink和m函数(Learning about the S function, SMVSC routine 3)

直流电机的转速，电流双闭环控制simulink仿真，包括整流桥(DC motor speed and current closed-loop control simulink simulation, including the bridge rectifier)

“Fast Tracking via Dense Spatio-Temporal Context Learning,” In ECCV 2014的源代码，效果非常好。(In this paper, we present a simple yet fast and robust algorithm which exploits the spatio-temporal context for visual tracking. Our approach formulates the spatio-temporal relationships between the object of interest and its local context based on a Bayesian framework, which models the statistical correlation between the low-level features (i.e., image intensity and position) from the target and its surrounding regions. The tracking problem is posed by computing a confidence map, and obtaining the best target location by maximizing an object location likelihood function. The Fast Fourier Transform is adopted for fast learning and detection in this work. Implemented in MATLAB without code optimization, the proposed tracker runs at 350 frames per second on an i7 machine. Extensive experimental results show that the proposed algorithm performs favorably against state-of-the-art methods in terms of efficiency, accuracy and robustness.)

kalman滤波，系统方程主要采用动态模型的例程(Kalman filtering, the system mainly uses dynamic equations of the model routines)

一个身体部位比较模型的新方法网络（BAN）的，可以容纳多个环节和多个科目。所述的绝对测量允许跨频谱可能刻画的比较 从单参数为整个合奏，通过基于参数化到每个活动，每个学科和每个环节模型。使用错误，并明确之间权衡复杂性，在一个善良的适应措施相结合，显示有重要的影响时，适用于一系列典型的禁止通道数据。它是有不同的 在模式的选择的影响，以及它相关的复杂性，混合活动的“日常”的数据，设置活动相比，动态数据（例如步行）。平均路径损耗的不足，甚至位数的路径损失的措施，作为唯一的表征还强调“禁止通道。 (A new approach to compare models for body area networks (BAN) that accommodates multiple links and multiple subjects is presented. The absolute measure described allows comparison across a spectrum of possible characterizations ranging from single-parameter for an entire ensemble, through to per-activity, per-subject and per-link based parameterized models. The use of an explicit trade-off between error and complexity, combined in a goodness-of-fit measure, is shown to have important consequences when applied to a range of typical BAN channel data. It is shown that there are different implications in choice of model, and it’s associated complexity, for mixed-activity “everyday” data, when compared with set-activity dynamic data (e.g. walking). The deficiency of mean path loss, or even median path loss measures, as a sole characterization of the BAN channel is also highlighted.)

解决OFDM中PAPR问题的MATLAB程序。(Solve the PAPR problem of OFDM in the MATLAB program.)

本程序是一维密度估计，用于了解和密度估计有很大帮助。(One-dimensional kernel density estimation )

this is simmulation QPSK modulation in AWGN channel