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- locally stationary Gaussian processes 局部平稳高斯过程
- stationary Gaussian process 稳定高斯过程
- Limiting Distribution for the Maxima of Stationary Gaussian Processes 平稳高斯过程最大值的极限分布
- The Limiting Behavior of Large Increments of Stationary Gaussian Processes 大增量平稳高斯过程的极限行为
- Asymptotic Independence of Maxima and Minima of Locally Stationary Gaussian Processes 局部平稳高斯过程的最大值与最小值的渐近独立性
- Polar Functions and Relative Dimension for d-Dimensional Stationary Gaussian Processes d维平稳高斯过程的极函数及其相关维数
- stationary Gaussian Processes 平稳高斯过程
- stationary gaussian markovian process 平稳高斯 马尔可夫过程
- This paper presents the source coding theorem for discrete-time stationary Gaussian sources with absolutely summable autocorrelation sequence. 摘要本论文提出具有绝对可加性自相关数列的离散时间稳定高斯讯号的编码定理。
- Therefore, boundedness condition on the spectrum, which is a common assumption in the earlier studies for stationary Gaussian sources, is lifted by the theorem. 因此，在以往研究离散时问稳定高斯讯号的编码定理中，通常具有的频谱必须有限的假设在本定理中可被去除。
- Research Areas: robotics, neural net, Gaussian process, scientific computing, and software/ hardware development. 主要研究领域为冗余机器人，递归神经网络，高斯过程，科学计算和软硬件开发。
- Research Areas: robotics, neural net, Gaussian process, scientific computing, and software/hardware development. 主要研究领域为冗余机器人，递归神经网络，高斯过程，科学计算和软硬件开发。
- Under the assumption that the claim-arrival process is the renewal process, Cox process, generalized compound Poisson process, Gamma process and inverse Gaussian process etc. 将理赔到达过程推广为更新过程、广义复合Poisson过程、Cox过程、Gamma过程和逆高斯过程等等。
- stationary Gaussian vector sequence 平稳高斯向量序列
- stationary Gaussian vector sequences 平稳高斯向量序列
- Non - stationary Gaussian sequence 非平稳高斯序列
- The Joint Limiting Distribution of Exceedances Point Process and Partial Sum of a Kind of Stationary Gaussian Sequences 一类平稳高斯序列超过数点过程与部分和的联合极限分布
- measuring earth magnetic field by Gaussian process 高斯法测地磁场
- Gaussian processes(GP) are probabilistic kernel machines and moderately simple to implement and use without loss of performance compared with other kernel methods. 高斯过程一种具有概率意义的核学习机,在不损失性能的条件下,与其它核方法相比,有着其容易实现的优点。
- Gaussian process latent variable model 高斯过程隐变量模型
