K-Means: Implementation and Analysis

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Achievable Rate & Capacity

Explores achievable rate, channel capacity, spectral efficiency, and fading channels in wireless communication systems.

Kernel K-means Clustering

Explores Kernel K-means clustering, interpreting solutions, handling missing data, and dataset selection for machine learning.

Environmental Legislation and Construction Law

Covers environmental legislation related to noise pollution and rules for noise protection.

Inverter DC Characteristics

Explains the DC characteristics of an inverter, including the switching threshold VM and noise margins.

Feature Extraction & Clustering Methods

Covers feature extraction, clustering, and classification methods for high-dimensional datasets and behavioral analysis using PCA, t-SNE, k-means, GMM, and various classification algorithms.

Application: Error Rate of PAM Signal

Explores the impact of noise on signal transmission and the calculation of error rates in communication systems.

Road Noise: Source-side Measures

Covers the analysis of road noise reduction measures at the source, focusing on different road coverings and speed reduction impact.

Noise Pollution: Impact and Mitigation Measures

Explores the impact of noise pollution, legal frameworks, noise sources, and mitigation measures.

Clustering: Unsupervised Learning

Explores clustering in high-dimensional space, covering methods like hierarchical clustering, K-means, and DBSCAN.

Quantum Sensing: Parameter Estimation and Bounds

Covers parameter estimation in quantum metrology, Quantum Fisher Information, Ramsey interferometry, entanglement, and noise impact on NooN states.