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Clustering is essential in data analysis and machine learning, but traditional algorithms like $k$-means and Gaussian Mixture Models (GMM) often fail with nonconvex clusters. To address the challenge, we introduce the Flexible Bivariate…

In recent years, thanks to the advances in meta-materials, the concept of continuous-aperture MIMO (CAP-MIMO) is reinvestigated to achieve improved communication performance with limited antenna apertures. Unlike the classical MIMO composed…

We propose Deep Residual Mixture Models (DRMMs), a novel deep generative model architecture. Compared to other deep models, DRMMs allow more flexible conditional sampling: The model can be trained once with all variables, and then used for…

The classic design of grid-forming control strategies for power converters rely on the stringent assumption of the timescale separation between DC and AC states and their corresponding control loops, e.g., AC and DC loops, power and…

A multicarrier-division duplex (MDD)-based cell-free (CF) scheme, namely MDD-CF, is proposed, which enables downlink (DL) data and uplink (UL) data or pilots to be concurrently transmitted on mutually orthogonal subcarriers in distributed…

In this paper, we propose an orthogonal frequency division multiplexing (OFDM)-based generalized optical quadrature spatial modulation (GOQSM) technique for multiple-input multiple-output optical wireless communication (MIMO-OWC) systems.…

We present the Gaussian process dynamical mixture model (GPDMM) and show its utility in single-example learning of human motion data. The Gaussian process dynamical model (GPDM) is a form of the Gaussian process latent variable model…

Multimodal learning integrates diverse modalities but suffers from modality imbalance, where dominant modalities suppress weaker ones due to inconsistent convergence rates. Existing methods predominantly rely on static modulation or…

Current wireless communication technologies are insufficient in the face of ever-increasing demands. Therefore, novel and high-performance communication systems are needed. In this paper, a novel high data rate and high-performance index…

We present a generative dialogue system capable of operating in a full-duplex manner, allowing for seamless interaction. It is based on a large language model (LLM) carefully aligned to be aware of a perception module, a motor function…

Partial feedback in multiple-input multiple-output (MIMO) communication systems provides tremendous capacity gain and enables the transmitter to exploit channel condition and to eliminate channel interference. In the case of severely…

In learning theory, a standard assumption is that the data is generated from a finite mixture model. But what happens when the number of components is not known in advance? The problem of estimating the number of components, also called…

Modelling of multivariate densities is a core component in many signal processing, pattern recognition and machine learning applications. The modelling is often done via Gaussian mixture models (GMMs), which use computationally expensive…

Massive multiple-input multiple-output (MIMO) is one of the key technologies in future generation networks. Owing to their considerable spectral and energy efficiency gains, massive MIMO systems provide the needed performance to cope with…

Multidimensional generalized quadrature index modulation scheme is proposed in this paper for conveying extra digital information with the aid of the space, radio frequency (RF) mirrors, and time indices. Explicitly, this proposed scheme…

Rendering dynamic reverberation in a complicated acoustic space for moving sources and listeners is challenging but crucial for enhancing user immersion in extended-reality (XR) applications. Capturing spatially varying room impulse…

In this paper, we consider the problem of preamble design in multiple-input multiple-output (MIMO) systems employing offset quadrature amplitude modulation based filter bank multicarrier (OQAM/FBMC) and propose a preamble optimization…

In this paper, we propose a feedback-efficient hybrid precoding framework for wideband millimeter-wave (mmWave) multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) systems. To mitigate the high cost of…

A multi-input multi-output based grid-forming (MIMO-GFM) converter has been proposed using multivariable feedback control, which has been proven as a superior and robust system using low-order controllers. However, the original MIMO-GFM…

The next generation of wireless networks will face different challenges from new scenarios. The main contribution of this paper is to show that Generalized Frequency Division Multiplexing (GFDM), as a baseline of flexible circular filtered…