本消隐非线性阈值的优化算法可以改进脉冲噪声检测算法的性能，进而大大改善OFDM系统在中压配电线脉冲噪声环境中的总体性能。
The optimization algorithm proposed can improve the performance of impulse detection algorithm; furthermore, heighten the overall performance of the OFDM receiver in impulsive noise environment.
为提高噪声环境下椭圆类物体形状检测算法的稳定性与准确性，本文提出非线性数据拟合模型结合交叉参考迭代的新思路。
To solve the problem of ellipse - object - shape parameters detection in noise image, a new detection algorithm using nonlinear data fitting model and cross-reference iterative method is proposed.
根据信号的循环平稳特性，本文提出一种加性高斯白噪声信道中基于循环频率估计的PS K信号存在性检测算法。
A presence detection algorithm based on the estimation of cyclic frequency for Phase Shift-Keying (PSK) signals in additive white Gaussian noise (AWGN) is proposed in this paper.
根据目标、噪声和背景边缘在小波域的不同特点，提出一种基于小波分析的红外小目标检测算法。
According to their different characteristics of the targets, noises and background edges in wavelet domain, a small target detection algorithm based on wavelet analysis is proposed.
由于人体器官所处的背景较为复杂，边缘检测算法容易受到噪声的干扰而效果不佳。
Because of intricate backgrounds of human organs, edge-detecting algorithms are liable to be invalid under noise.
针对语音激活检测的鲁棒性问题，提出在非平稳噪声环境下使用基于复高斯混合模型的鲁棒语音激活检测算法。
In order to improve the robustness of voice activity detection (VAD), the use of an algorithm based on complex Gaussian mixture model under nonstationary noisy environments was presented.
为了在不同噪声、信噪比下为基音检测算法提供更能准确反映基音周期实际变化的输入语音，本文将信号分解思想引入基音检测前端处理中。
In order to provide an accurate-pitch-cycle speech for pith detection algorithm with varied noise and SNR, we use signal decomposition theory in pre-processing of pitch detection.
本文将小波包变换用于非高斯噪声统计特性的研究，提出一种新的非高斯分布噪声下的信号检测算法。
In the dissertation, it puts wavelet-packet decomposition into the study on non-gaussian noise. It offers a new signal dection method under non-gaussian noise backgroud.
研究了对局部平稳高斯色噪声混响模型和以局部平稳高斯色噪声混响模型为基础的分段匹配滤波和分段预白化匹配滤波检测算法。
Secondly, local stationary colored reverberation model and the block matched filtering and block prewhiten matched filtering detection methods which based on the model is studied.
词边界检测误差是语音识别中产生错误的主要原因之一，常规的检测算法在低信噪比尤其在背景噪声能量可变的环境下不能有效工作。
A major cause of errors in speech recognition is the inaccurate detection of word bound-ary. Conventional methods can not work well in the condition of low SNR and variable background noise level.
本文方法保留了最大-最小值方法去除随机脉冲噪声的优点，且检测算法简单，去噪快速有效。
The experiments show that the proposed method retains the merits of maximum-minimum method and is simple and effective in random impulsive noise removal.
基于小波变换的多尺度边缘提取算法，有效地弥补了传统的边缘检测算法的不足，在有效地抑制噪声的同时，提供了较高的边缘定位精度。
Research on image detection based on wavelet makes up the disadvantage in the traditional edge detection and improves the edge localization precision avoiding noise effectively.
实验结果表明，与传统边缘检测算法相比，该算法在保持图像边缘清晰的同时。有很强的去除噪声能力。
Experimental result indicates that the new edge detection achieves better image processing effect than traditional method, has strong ability of eliminating noise as well as keeps clear image edge.
分析了红外小目标图像的时域特性以及小目标、噪声、背景的不同特点，提出了一种时空结合的红外小目标检测算法。
The temporal domain characteristic of the infrared image and different features of small targets, noise and background were analyzed in this paper.
该文主要研究了受不同噪声污染图像的边缘提取问题，提出了一种基于模糊理论的边缘检测算法。
This paper mainly studies the edge detection of noisy images. An edge detector based on the fuzzy theory is presented.
该文主要研究了受不同噪声污染图像的边缘提取问题，提出了一种基于模糊理论的边缘检测算法。
This paper mainly studies the edge detection of noisy images. An edge detector based on the fuzzy theory is presented.
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