Description: 《Fundamentals of Statistical Signal Processing》(《随机信号处理基础》)的配套MATLAB源代码。为电信工程师、教师、和学生而设计。-"Fundamentals of Statistical Signal Proc essing "(" Random signal processing based ") supporting MATLAB code. To the telecommunication engineers, teachers, and students designed. Platform: |
Size: 5656 |
Author:萨木 |
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Description: 《Fundamentals of Statistical Signal Processing》(《随机信号处理基础》)的配套MATLAB源代码。为电信工程师、教师、和学生而设计。-"Fundamentals of Statistical Signal Proc essing "(" Random signal processing based ") supporting MATLAB code. To the telecommunication engineers, teachers, and students designed. Platform: |
Size: 5120 |
Author:萨木 |
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Description: 这是一本很好的统计信号处理英文原著,比较基础,pdf格式,-This is a very good statistical signal processing in English original, more basic, pdf format, Platform: |
Size: 1564672 |
Author:李杰 |
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Description: Solution Manual to Fundamentals of Statistical Signal Processing - Estimation Theory
By Steven M.Kay Platform: |
Size: 4836352 |
Author:Giuseppe |
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Description: Solution Manual to Fundamentals of Statistical Signal Processing - Detection Theory
By Steven M.Kay Platform: |
Size: 5568512 |
Author:Giuseppe |
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Description: 哈佛大學的Fundamentals of Statistical Signal Processing上課資料-Harvard Fundamentals of Statistical Signal Processing class information Platform: |
Size: 125952 |
Author:張良 |
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Description: Laussane大學的Fundamentals of Statistical Signal Processing上課資料-Laussane University Fundamentals of Statistical Signal Processing class information Platform: |
Size: 592896 |
Author:張良 |
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Description: Fundamentals of Statistical Signal Processing-The Fundamentals of Statistical Signal Processing Platform: |
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Author:VRGdbcij+295656 |
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Description: Fundamentals of Statistical Signal Processing-The Fundamentals of Statistical Signal Processing Platform: |
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Author:lzps_3132 |
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Description: Fundamentals of Statistical Signal Processing: Estimation Theory
In this project, we consider the problem of estimating a parameter associated with
the local oscillator leakage of a RF receiver by tone test. For this reason, an approxi-
mate maximum-likelihood (ML) estimator is proposed. It's error performance is analyzed
by Monte-Carlo (MC) simulations and compared to the theoretical Cramer-Rao Lower
Bounds. Platform: |
Size: 3307 |
Author:xinghezhifeng |
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