| 1. | A primary study on the detection of weak signal in a stronger noise background
色噪声背景下微弱周期脉冲信号的混沌检测方法 |
| 2. | Chaos - based weak periodic pulse signal detection approach under colored noise background
强噪声背景中微弱信号检测的初步研究 |
| 3. | An improved method of detecting abrupt information based on singularity value decomposition in noise background
噪声背景下检测突变信息的奇异值分解技术 |
| 4. | Two - dimensional harmonics frequency estimation in additive gaussian noise background based on quaternion and hypercomplex
四元数和超复数在加性高斯噪声背景下二维谐波频率估计中的应用 |
| 5. | And the simulation for summarize the pd signals from strong noise background is conducted in matlab5 . 3 ' s wavelet - transform toolbox , satisfied result is gotten
具体针对并联电容器，对模拟的采集信号在matlab5 . 3环境下做仿真，四川大学硕士学位论文提取出淹没在噪声中的局部放电信号。 |
| 6. | A tv target tracing system has following features : real - time , image indistinctness on the ground of dynamic tracing and external environmental distortion , high noise background intensity and so on
电视目标跟踪系统实时性强，由于是动态跟踪和外界环境干扰，所以导致图像不清晰、背景噪声较强。 |
| 7. | From the objects recognition tests buried in strong noise background , we found even with the ann post - processing technique , a certain amount of recognition errors ( about 10 % ) were still unavoidable
通过对处于复杂背景噪声干扰中的目标的识别测试发现，即使采用ann相关信号后处理技术， opr系统仍会存在一定程度的误识别( 10 ) 。 |
| 8. | The purpose of eeg signal processing is to extract the hidden or weak patterns that probably have some physiological and / or psycho - physiological significance from eeg signals in sophisticated noise background and then to apply them to the research on clinical medicine or cognitive science
我们对脑电信号处理的目的就是为了从复杂的背景噪声中分离出有用的脑电信号，进而从中提取出具有明确生理意义的脑电特征，并应用于临床医学和脑认知科学的研究。 |
| 9. | The paper presents a detailed scheme on the reliable recognition of the ultrasonic echo - signal in high noise background . based on the scheme , a detailed discussion of the application of the traditional digital processing methods in this field is proposed in this paper . based on the traditional methods of wavelet analysis , some of novel algorithms are also proposed in the paper and have been programmed using matlab
本文对高噪声背景下超声回波信号的可靠识别问题进行了深入研究，讨论了经典数字处理方法应用于这个问题的不足之处，并在小波分析的几种传统方法的讨论基础上，做了几点改进，以适合所要解决的超声回波信号的可靠识别问题，并进行了程序实现。 |
