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含噪信号的可变潜伏期：脑电位数据的估计与检验AI 解读

The electric response of the brain related to some event, i.e. stimulus, is usually estimated by repeated stimulation and subsequent averaging of the activity recorded time-locked to the stimulus. The present paper deals with the model that the single responses may have varying latency, i.e. arrival time, after stimulus onset. For estimating the single latencies, a maximum likelihood approach employing iterative Fisher-scoring is developed. Further a statistic for testing on…

含噪信号的可变潜伏期：脑电位数据中的估计与检验AI 解读

The electric response of the brain related to some event, i.e. stimulus, is usually estimated by repeated stimulation and subsequent averaging of the activity recorded time-locked to the stimulus. The present paper deals with the model that the single responses may have varying latency, i.e. arrival time, after stimulus onset. For estimating the single latencies, a maximum likelihood approach employing iterative Fisher-scoring is developed. Further a statistic for testing on…

重复刺激诱发的含噪信号同质性检验AI 解读

Two statistics are proposed for testing the homogeneity of signals, when these are noisy and repeatedly recorded. The distribution of the statistics is well approximated by the $\chi^2$ and the normal distribution, respectively, as shown by theoretical and simulation results. Power and insensitivity to other types of variation are discussed. The approach is developed in the context of analysing recordings of electric brain potentials being evoked by some stimulation, as…

平稳点过程谱参数的估计AI 解读

This paper considers the two approaches for estimating the parameters specifying the spectral density of the counting process of a stationary point process, namely the frequency domain and the time domain approaches. The relation between the two is clarified; consistency and asymptotic normality of the estimates are established. Finally the special case of a rational spectral density is considered in some detail.