In this paper, a novel Gaussian mixture regression model (GMRM) is proposed to model the unknown non-Gaussian measurement likelihood for Bayesian update to achieve nonlinear state estimation. Without any prior assumption or limitation of measurement noises' statistics and distributions, the GMRM can ...
3.2.4 Gaussian mixture regression The regression process has the goal of continuously estimating the robot joints bending angles. The Gaussian mixture regression (GMR) provides a smooth generalized version of the signal starting from the GMM. GMR estimates the joint angles αˆ and their covariance...
Gaussian mixture model Gaussian mixture regression Haptics Lossy compression Motion-copying system Skill acquisition ASJC Scopus subject areas Computer Science Applications Electrical and Electronic Engineering Cite this APA Standard Harvard Vancouver Author ...
This paper presents a new data-driven model of length-pressure hysteresis of pneumatic artificial muscles (PAMs) based on Gaussian mixture models (GMMs). By ignoring the high-order dynamics, the hysteresis of PAMs is modeled as a first-order nonlinear dynamical system based on GMMs, and inversio...
The most common approach is to postulate a proportion p of immunes or long-term survivors and to use a mixture model [5]. This paper introduces the defective inverse Gaussian model as a cure model and examines the use of the Gibbs sampler together with a data augmentation algorithm to ...
In addition, three state-of-the-art models: autoregressive moving average, generalized linear regression, and artificial neural networks, were developed for drought forecasting served as a comparison. The forecasting abilities were evaluated using four types of verification methods with respect to the ...
从中心极限定理的角度上看,把混合模型假设为高斯的是比较合理的,当然也可以根据实际数据定义成任何分布的Mixture Model,不过定义为高斯的在计算上有一些方便之处,另外,理论上可以通过增加Model的个数,用GMM近似任何概率分布。 混合高斯模型的定义为: 其中K为模型的个数,πk为第k个高斯的权重,则为第k个高斯的概率...
In step one of the algorithm, we model the normalized Hi-C data matrix by a two-component Gaussian mixture model (Fig. 1a). Our rationale is that observed chromatin contacts can be categorized into two types: “intra-domain contact” and “inter-domain contact”. We denote the normalized ...
The establishment of an accurate and reliable forecasting model is important for water resource planning and management. In this study, we developed a hybrid model (namely GMM-XGBoost), coupling extreme gradient boosting (XGBoost) with Gaussian mixture model (GMM), for monthly streamflow forecasting....
Gaussian mixture continuously adaptive regression for multimode processes soft sensing under time-varying virtual drift 2023, Journal of Process Control Citation Excerpt : Moreover, continuous processes generate streaming industrial big data [20], and the property of data streams may change over time du...