-
BP
说明: bp神经网络的源程序,很实用,很不错的!(bp neural network source code, very practical, very good!)
- 2009-09-23 08:30:22下载
- 积分:1
-
MATLAB-MingLingDaQuan
姚东等编著的Matlab命令大全,适合初学者使用。(YAO Dong-ed, such as the Matlab command Daquan, suitable for beginners to use.)
- 2009-03-09 16:12:26下载
- 积分:1
-
matlab2
MATLAB 课本实例教程MATLAB 课本实例教程MATLAB 课本实例教程MATLAB 课本实例教程(MATLAB)
- 2009-12-23 09:00:48下载
- 积分:1
-
mckd
峭度相关最大化解卷积(MCKD),可以用来设计滤波器,提取噪声背景下的冲击成分(maximum related Kurtosis deconvolution (MCKD), can be used to design a filter to extract the impact of background noise component)
- 2020-11-05 16:29:50下载
- 积分:1
-
LTE_downlink
LTE 下行链路系统代码 含信道估计,编解码以及频偏估计模块(LTE downlink system including channel estimation code)
- 2020-12-10 15:29:17下载
- 积分:1
-
lizilvbo_matlab
粒子滤波的matlab程序~ 希望对大家有用哈~(Particle filter matlab program)
- 2012-01-15 18:11:59下载
- 积分:1
-
hv_2d
说明: 对二维情况下的Pareto进行指标分析,主要分析超体积指标(Hypervolume),平均欧几里得距离(Mean Euclidian Distance)和均匀度(Spacing Index)(This paper analyzes the Pareto index in two-dimensional situation, mainly including the hypervolume, mean Euclidean distance and spacing index)
- 2021-03-19 21:49:18下载
- 积分:1
-
QAMPModemPDemo
说明: 基于MATLAB/GUI的M-QAM调制解调及误码率,本文件是在MATLAB2009a版本上设计的,低于此版本的有可能会出错。
此文件中“M_QAM.m”是主文件,其他均为调用文件,该程序实现了MQAM的调制解调功能,并画出了每一步的波形
(Based on MATLAB/GUI s M-QAM modulation and demodulation and bit error rate, this document is designed MATLAB2009a version, this version is lower than might be wrong. This file is in the " M_QAM.m" is the main document, others are calling the file, the program implements the MQAM modulation and demodulation functions, and draw the waveform of each step)
- 2011-03-30 00:19:50下载
- 积分:1
-
tracking_doa
用于智能天线中自适应的移动目标的跟踪,其中有卡尔曼滤波的源代码(for smart antenna adaptive tracking moving targets, including Kalman filtering source code)
- 2020-06-28 15:20:02下载
- 积分:1
-
src-fusion
A. Fusion at the Feature Extraction Level
The data obtained from each sensor is used to compute a
feature vector. As the features extracted from one biometric
trait are independent of those extracted from the other, it is
reasonable to concatenate the two vectors into a single new
vector. The primary benefit of feature level fusion is the
detection of correlated feature values generated by different
feature extraction algorithms and, in the process, identifying a salient set of features that can improve recognition accuracy
[14]. The new vector has a higher dimension and represents the
identity of the person in a different hyperspace. Eliciting this
feature set typically requires the use of dimensionality
reduction/selection methods and, therefore, feature level fusion
assumes the availability of a large number of training data.
- 2013-03-14 16:40:42下载
- 积分:1