-
matlab
histogram of oriented gradient
- 2010-10-18 18:10:02下载
- 积分:1
-
embeded_system_realize_with_c
说明: 嵌入式系统的建模及matlab仿真,同时给出相应的C++实现代码(failed to translate)
- 2009-08-12 09:46:53下载
- 积分:1
-
ssaaxa
this source code is sdsasa matlab
- 2013-08-04 18:05:16下载
- 积分:1
-
Sattellite4
code for sattelite calculaton
- 2013-09-14 17:33:51下载
- 积分:1
-
codes
this file give different codes of modulation
- 2013-12-04 04:40:35下载
- 积分:1
-
Integration
信号处理中的积分运算,以位移、速度和加速度为例,适用于matlab。(Signal processing integration operation of displacement, velocity and acceleration, for example, apply to matlab.)
- 2016-03-10 11:33:24下载
- 积分:1
-
1
说明: 现代海战需要功能综合的作战平台和性能优良的
武器系统来应对,海战场复杂多维的环境因素对海上
兵力运用有很大的影响。因此,如何准确建立海战场
的评估指标体系并进行科学评判是指挥员做出决策的
重要前提。目前,海战场环境评估的方法有层次分析
法、模糊评判法、指数法等11’21。针对这些方法主观性
比较强等不足,本文引入云重心的评估方法简单易行,
科学有效,可操作性强。
基于云重心方法的海战场环境评估(Modern naval warfare needs integrated operational platforms and excellent weapon systems to cope with. The complex and multi-dimensional environmental factors of naval battlefield have a great impact on the use of naval forces. Therefore, how to accurately establish the evaluation index system of sea battlefield and make scientific evaluation is an important prerequisite for commanders to make decisions. At present, the methods of Marine Battlefield Environment Assessment include analytic hierarchy process, fuzzy evaluation, index method and so on. In view of these shortcomings, such as strong subjectivity, this paper introduces cloud gravity center evaluation method which is simple, scientific and effective, and operable. Sea Battlefield Environment Assessment Based on Cloud Barycenter Method)
- 2019-03-21 14:39:09下载
- 积分:1
-
HW_5
Generation of Binomial random variables from uniform random variable
- 2010-06-11 21:21:49下载
- 积分:1
-
PARReductioninOFDMviaActiveConstellationExtension
ACE technique for reduction PAPR in OFDM system.
This is project main for ACE technique.
- 2010-12-23 20:21:54下载
- 积分:1
-
main
We formulate a scheduling problem that takes into account different hardware delays experienced by the secondary users
(SUs) in a centralized cognitive radio network (CRN) while switching to different frequency bands. We propose a polynomial-time
suboptimal algorithm to address our formulated scheduling problem. We evaluate the impact of varying switching delay, number of
frequencies, and number of SUs. Our simulation results indicate that our proposed algorithm is robust to changes in the hardware
spectrum switching delay and its performance is very close to its upper bound. We also compare our proposed method with the
corresponding constant switching delay-based algorithm and demonstrate that our suggestion of taking into account the different
hardware delays while switching to different frequency bands is essential for scheduling in CRNs.
- 2013-10-07 12:36:59下载
- 积分:1