<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[cassiopeia515的博客]]></title><description><![CDATA[]]></description><link>https://blog.youkuaiyun.com/cassiopeia515</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; cassiopeia515]]></copyright><item><title><![CDATA[现代滤波器的综合应用]]></title><link>https://blog.youkuaiyun.com/cassiopeia515/article/details/157022592</link><guid>https://blog.youkuaiyun.com/cassiopeia515/article/details/157022592</guid><author>cassiopeia515</author><pubDate>Thu, 05 Feb 2026 17:35:25 +0800</pubDate><description><![CDATA[从仿真结果频谱图可以看出，与接收信号相比，测试信号经过维纳滤波、卡尔曼滤波和LMS均衡后，频偏校正和频谱拓宽现象得到明显改善。]]></description><category></category></item><item><title><![CDATA[无约束优化问题的信赖域求解方法]]></title><link>https://blog.youkuaiyun.com/cassiopeia515/article/details/155036792</link><guid>https://blog.youkuaiyun.com/cassiopeia515/article/details/155036792</guid><author>cassiopeia515</author><pubDate>Fri, 19 Dec 2025 11:46:59 +0800</pubDate><description><![CDATA[从仿真结果可以看出，当初始值为（1，-1）时，算法迭代10次即可获得最优结果。与梯度法对比，信赖域法求解无约束最优化问题的迭代次数明显减少，且目标函数最有解更接近精确解。]]></description><category></category></item><item><title><![CDATA[锁相环原理及其matlab仿真]]></title><link>https://blog.youkuaiyun.com/cassiopeia515/article/details/153830533</link><guid>https://blog.youkuaiyun.com/cassiopeia515/article/details/153830533</guid><author>cassiopeia515</author><pubDate>Sat, 01 Nov 2025 00:17:46 +0800</pubDate><description><![CDATA[从仿真结果可以看出，锁相环vco的输出频率为1000.98Hz，与参考频率的误差为0.98Hz.经过0.06s后，锁相环进入锁定状态。]]></description><category></category></item><item><title><![CDATA[维纳滤波器及其matlab仿真]]></title><link>https://blog.youkuaiyun.com/cassiopeia515/article/details/148794500</link><guid>https://blog.youkuaiyun.com/cassiopeia515/article/details/148794500</guid><author>cassiopeia515</author><pubDate>Fri, 20 Jun 2025 16:01:07 +0800</pubDate><description><![CDATA[示例中原始信号为标准正弦信号，噪声为随机高斯白噪声。从仿真结果可以看出，维纳滤波后信号信噪比大大提高。]]></description><category></category></item><item><title><![CDATA[符号速率估计——小波变换法]]></title><link>https://blog.youkuaiyun.com/cassiopeia515/article/details/147431382</link><guid>https://blog.youkuaiyun.com/cassiopeia515/article/details/147431382</guid><author>cassiopeia515</author><pubDate>Tue, 22 Apr 2025 22:23:45 +0800</pubDate><description><![CDATA[从仿真结果可以看出，小波变换法估计出的符号速率为5.00126，与信号的实际符号速率5基本接近，同时，符号速率估计的精度受信号的频率以及Haar小波的参数影响。]]></description><category></category></item><item><title><![CDATA[MPSK载波信号在awgn信道下的误码率]]></title><link>https://blog.youkuaiyun.com/cassiopeia515/article/details/146541865</link><guid>https://blog.youkuaiyun.com/cassiopeia515/article/details/146541865</guid><author>cassiopeia515</author><pubDate>Wed, 26 Mar 2025 22:03:36 +0800</pubDate><description><![CDATA[由仿真结果可以看出，载波信号的误码率BPSK<QPSK<8PSK,随着信噪比的增加，MPSK载波信号的误码率理论值与仿真值越来约接近。]]></description><category></category></item><item><title><![CDATA[数字调制方式识别-基于特征参数提取的判决树法]]></title><link>https://blog.youkuaiyun.com/cassiopeia515/article/details/145937301</link><guid>https://blog.youkuaiyun.com/cassiopeia515/article/details/145937301</guid><author>cassiopeia515</author><pubDate>Fri, 28 Feb 2025 21:36:59 +0800</pubDate><description><![CDATA[本实例中在形成判决树时门限值为参考论文中给出的门限值，同时在计算δafδaf​和δapδap​时没有考虑对弱信号的处理，因此，识别结果准确率较低，需进一步改进。]]></description><category></category></item><item><title><![CDATA[符号速率估计——延迟相乘法]]></title><link>https://blog.youkuaiyun.com/cassiopeia515/article/details/145287410</link><guid>https://blog.youkuaiyun.com/cassiopeia515/article/details/145287410</guid><author>cassiopeia515</author><pubDate>Wed, 05 Feb 2025 16:04:45 +0800</pubDate><description><![CDATA[如图所示，利用延迟相乘法估计的符号速率为100bps，与仿真中设置的符号速率一致。]]></description><category></category></item><item><title><![CDATA[Kalman滤波原理及Matlab代码实现]]></title><link>https://blog.youkuaiyun.com/cassiopeia515/article/details/144774408</link><guid>https://blog.youkuaiyun.com/cassiopeia515/article/details/144774408</guid><author>cassiopeia515</author><pubDate>Sat, 28 Dec 2024 17:55:08 +0800</pubDate><description><![CDATA[而在期望响应未知的情况下，要想进行线性最优滤波，可从状态空间的角度出发，利用基于状态空间模型的线性最优滤波器，即Kalman滤波器。其中，x(n)表示离散系统n时刻的状态向量，是不可观测的；F(n+1,n)表示从n时刻到n+1时刻的状态转移矩阵，是已知的；,y(n),求状态向量x(i)各个分量的最小二乘估计。考虑一步预测问题，利用观测数据向量y(1),y(2),…,y(n),求观测向量y(n)的最小二乘估计,记作。其中，y(n)为n时刻观测向量，C(n)为观测矩阵，，而是先计算状态向量x(n)的一步预测。]]></description><category></category></item><item><title><![CDATA[RLS自适应滤波与Matlab仿真]]></title><link>https://blog.youkuaiyun.com/cassiopeia515/article/details/143772069</link><guid>https://blog.youkuaiyun.com/cassiopeia515/article/details/143772069</guid><author>cassiopeia515</author><pubDate>Fri, 15 Nov 2024 10:07:40 +0800</pubDate><description><![CDATA[RLS自适应滤波与Matlab仿真。]]></description><category></category></item><item><title><![CDATA[无约束非线性优化问题——牛顿法]]></title><link>https://blog.youkuaiyun.com/cassiopeia515/article/details/143382711</link><guid>https://blog.youkuaiyun.com/cassiopeia515/article/details/143382711</guid><author>cassiopeia515</author><pubDate>Thu, 31 Oct 2024 11:13:33 +0800</pubDate><description><![CDATA[从仿真结果中可以看出，牛顿法的迭代次数约为15次，最优解的误差小于1e-16，迭代次数和误差值明显优于梯度法，初始值的选取对算法的性能影响也较小。牛顿法的原理是利用一阶导数（梯度）和二阶导数（Hess）对目标函数进行二次函数近似，把二次函数的极小值当成新的迭代点，不断重复，从而找到最优解。]]></description><category></category></item><item><title><![CDATA[无约束非线性优化问题——梯度法]]></title><link>https://blog.youkuaiyun.com/cassiopeia515/article/details/142567154</link><guid>https://blog.youkuaiyun.com/cassiopeia515/article/details/142567154</guid><author>cassiopeia515</author><pubDate>Fri, 27 Sep 2024 09:13:08 +0800</pubDate><description><![CDATA[从梯度法求解目标值的结果来看，算法的收敛需要160次迭代以上，收敛速度比较缓慢。选择合适的初始值，有利于提高算法的收敛速度。在求解时一般通过不同的方式确定步长和搜索方向来确定最优解，梯度法是用负梯度方向来作为搜索方向的。(3)由线搜索方法确定步长因子。附近连续可微，为搜索方向向量，最速下降法的迭代公式是。无约束非线性优化问题。]]></description><category></category></item><item><title><![CDATA[自适应均衡器——时域实现]]></title><link>https://blog.youkuaiyun.com/cassiopeia515/article/details/142134464</link><guid>https://blog.youkuaiyun.com/cassiopeia515/article/details/142134464</guid><author>cassiopeia515</author><pubDate>Thu, 12 Sep 2024 10:36:29 +0800</pubDate><description><![CDATA[通信系统中，由于多径效应、信道带宽的有限性及信道特性的不完善导致数据通过信道时不可避免地产生码间串扰。用均衡技术来补偿码间干扰的处理器称为均衡器，均衡包括时域均衡和频域均衡，在时变无线信道中，几乎全部采用时域的实现方式。二进制双极性码元经过信道衰落之后，在不同的信噪比下，统计均衡前后信号的误码率，随着信号信噪比的提升，均衡后接收端误码率明显降低。可见，横向滤波器的输出y(t)为输入x(t)经过2N+1个不同时延单元之后的加权和。为了消除码间干扰，应该选取合适的均衡器系数，使得以k为中心的前后2N个符号。]]></description><category></category></item><item><title><![CDATA[通信信号瞬时参数的测量——FSK]]></title><link>https://blog.youkuaiyun.com/cassiopeia515/article/details/141036691</link><guid>https://blog.youkuaiyun.com/cassiopeia515/article/details/141036691</guid><author>cassiopeia515</author><pubDate>Fri, 09 Aug 2024 10:15:12 +0800</pubDate><description><![CDATA[通信信号的瞬时参数可用于信号的分析识别，通过利用希尔伯特变换，得到信号的正交分量，根据实部与虚部的关系，计算信号的瞬时参数：如瞬时幅度、瞬时相位、瞬时频率等。示例中采样4FSK信号，频移间隔为2MHz，仿真结果符合预期。注意，瞬时相位的计算需解混叠。使用差分法，由信号的瞬时相位得瞬时频率。以4FSK信号为例，对信号瞬时参数进行分析测量。]]></description><category></category></item><item><title><![CDATA[信号带宽、电平的测量]]></title><link>https://blog.youkuaiyun.com/cassiopeia515/article/details/140813906</link><guid>https://blog.youkuaiyun.com/cassiopeia515/article/details/140813906</guid><author>cassiopeia515</author><pubDate>Wed, 31 Jul 2024 10:44:37 +0800</pubDate><description><![CDATA[[TOC]信号带宽、电平的测量。]]></description><category></category></item><item><title><![CDATA[无线电测向——最大信号法]]></title><link>https://blog.youkuaiyun.com/cassiopeia515/article/details/140801225</link><guid>https://blog.youkuaiyun.com/cassiopeia515/article/details/140801225</guid><author>cassiopeia515</author><pubDate>Tue, 30 Jul 2024 17:34:04 +0800</pubDate><description><![CDATA[无线电测向——最大信号法。]]></description><category></category></item><item><title><![CDATA[信号载频的测量——时域算法]]></title><link>https://blog.youkuaiyun.com/cassiopeia515/article/details/140764972</link><guid>https://blog.youkuaiyun.com/cassiopeia515/article/details/140764972</guid><author>cassiopeia515</author><pubDate>Mon, 29 Jul 2024 11:43:25 +0800</pubDate><description><![CDATA[[TOC]信号载频的测量-时域算法。]]></description><category></category></item><item><title><![CDATA[信号载频的测量——频域算法]]></title><link>https://blog.youkuaiyun.com/cassiopeia515/article/details/140736045</link><guid>https://blog.youkuaiyun.com/cassiopeia515/article/details/140736045</guid><author>cassiopeia515</author><pubDate>Sat, 27 Jul 2024 16:50:33 +0800</pubDate><description><![CDATA[[TOC]信号载频的测量——频域算法。]]></description><category></category></item><item><title><![CDATA[LMS自适应滤波模型与matlab仿真]]></title><link>https://blog.youkuaiyun.com/cassiopeia515/article/details/140625284</link><guid>https://blog.youkuaiyun.com/cassiopeia515/article/details/140625284</guid><author>cassiopeia515</author><pubDate>Tue, 23 Jul 2024 10:54:45 +0800</pubDate><description><![CDATA[LMS模型仿真]]></description><category></category></item><item><title><![CDATA[现代信号处理第二版 张贤达]]></title><link>https://blog.youkuaiyun.com/cassiopeia515/article/details/139863454</link><guid>https://blog.youkuaiyun.com/cassiopeia515/article/details/139863454</guid><author>cassiopeia515</author><pubDate>Fri, 21 Jun 2024 16:09:09 +0800</pubDate><description><![CDATA[多重信号分类（MUSIC）重构信号]]></description><category></category></item></channel></rss>