由于MQAM信号的概率密度函数服从莱斯分布，从而用莱斯分布来构造识别算法。
Because the probability density function of MQAM signal obeys L-S distribution, so it may construct the algorithm of discerning with L-S distribution.
根据信号、本底的时间分布以及时间、时间误差、质量、质量差等变量之间的关系，构建概率密度函数。
The probability density function (PDF) is constructed from the time distributions of signal and backgrounds and the relations among time, time uncertainty, mass, and mass difference variables.
利用概率密度技术捕捉声信号的微小变化，能够有效地识别气侵并报警。
The possibility density technology was used to entrap a little change of acoustical signal, which can discern the gas incursion and give the alarm efficaciously.
它是建立在阵列输出信号和噪声参数联合后验概率密度基础上的空间谱估计。
It is established on the expected value of the theoretical spatial spectrum over the joint posterior density function of the array output signal and noise parameters.
在信号处理时把该信号看作随机的动态信号，采用概率密度和统计学的方法进行分析，从而预测出稠油油井出砂趋势。
The vibration signal is processed as stochastic dynamic signal and analyzed by the method of probability density and statistics, thus the trend of sand production of heavy oil-well.
但若假设的概率密度函数与真实概率密度函数差异较大，源信号将不能被正确分离。
If the assumed PDF is different from the true PDF considerably, the sources will not be separated correctly.
但若假设的概率密度函数与真实概率密度函数差异较大，源信号将不能被正确分离。
If the assumed PDF is different from the true PDF considerably, the sources will not be separated correctly.
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