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Novel approach for ECG separation using adaptive constrained IVABMGGMM
In this paper, we introduce the constrained independent vector analysis integrated with the
bounded multivariate generalized Gaussian mixture model (cIVABMGGMM) to tackle the …
bounded multivariate generalized Gaussian mixture model (cIVABMGGMM) to tackle the …
[HTML][HTML] Unsupervised Mixture Models on the Edge for Smart Energy Consumption Segmentation with Feature Saliency
Smart meter datasets have recently transitioned from monthly intervals to one-second
granularity, yielding invaluable insights for diverse metering functions. Clustering analysis, a …
granularity, yielding invaluable insights for diverse metering functions. Clustering analysis, a …
Automatic music mood classification using multi-modal attention framework
Automatic music recommendation systems based on human emotions are becoming
popular nowadays. Since audio and lyrics can provide a rich set of information regarding a …
popular nowadays. Since audio and lyrics can provide a rich set of information regarding a …
Bounded asymmetric gaussian mixture-based hidden markov models
Abstract Hidden Markov models (HMMs) have been widely applied in machine learning to
model diversified and heterogeneous time series data. In this chapter, integration of the …
model diversified and heterogeneous time series data. In this chapter, integration of the …
Multivariate Bounded Support Kotz Mixture Model with Minimum Message Length Criterion
In this paper, we present a multivariate bounded Kotz mixture model (BKMM) for data
modeling when the data lies in a bounded support region. In BKMM, parameter estimation is …
modeling when the data lies in a bounded support region. In BKMM, parameter estimation is …
A Gaussian hybrid clustering-based method for compensating for the loss of semi-persistent scheduling data in the middle station of large power grid regulation and …
L **ng, W Sun, Y Chen, W Shi, Z Zou… - Computers and Electrical …, 2024 - Elsevier
In order to ensure the effectiveness of power grid scheduling decisions, ensure the stability,
safety, and intelligence level of scheduling operations, and solve the semi persistent …
safety, and intelligence level of scheduling operations, and solve the semi persistent …
Model selection criterion for multivariate bounded asymmetric gaussian mixture model
In this paper, model selection criterion for bounded support asymmetric Gaussian mixture
model (BAGMM) using minimum message length (MML) is proposed. The proposed …
model (BAGMM) using minimum message length (MML) is proposed. The proposed …
Enhancing Human Action Recognition with Asymmetric Generalized Gaussian Mixture Model-Based Hidden Markov Models and Bounded Support
Human action recognition (HAR) is a crucial research field that necessitates the
implementation of advanced mathematical concepts to recognize human activities from …
implementation of advanced mathematical concepts to recognize human activities from …
Explainable Robust Smart Meter Data Clustering for Improved Energy Management
The widespread deployment of smart meters in residential settings has led to a wealth of
high-resolution electrical power consumption data, providing the opportunity to discover …
high-resolution electrical power consumption data, providing the opportunity to discover …
Automatic music mood classification using multi-modal attention framework
S AS, M JB, R Rajan - 2024 - dl.acm.org
Automatic music recommendation systems based on human emotions are becoming
popular nowadays. Since audio and lyrics can provide a rich set of information regarding a …
popular nowadays. Since audio and lyrics can provide a rich set of information regarding a …