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Found 10 papers, 2 papers with code
Extreme Point Pursuit -- Part II: Further Error Bound Analysis and Applications
In the first part of this study, a convex-constrained penalized formulation was studied for a class of constant modulus (CM) problems.
Extreme Point Pursuit -- Part I: A Framework for Constant Modulus Optimization
This study develops a framework for a class of constant modulus (CM) optimization problems, which covers binary constraints, discrete phase constraints, semi-orthogonal matrix constraints, non-negative semi-orthogonal matrix constraints, and several types of binary assignment constraints.
CLAPSep: Leveraging Contrastive Pre-trained Models for Multi-Modal Query-Conditioned Target Sound Extraction
Such systems consist of two components: a query network that converts user queries into conditional embeddings, and a separation network that extracts the target sound based on conditional embeddings.
Ranked #1 on
Target Sound Extraction
on AudioSet
Extending Whisper with prompt tuning to target-speaker ASR
Target-speaker automatic speech recognition (ASR) aims to transcribe the desired speech of a target speaker from multi-talker overlapped utterances.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
A Spatial Sigma-Delta Approach to Mitigation of Power Amplifier Distortions in Massive MIMO Downlink
A symbol-level precoding (SLP) scheme and a zero-forcing (ZF) precoding scheme, with the new design requirement by the spatial $\Sigma \Delta$ approach being taken into account, are developed.
Accelerated and Deep Expectation Maximization for One-Bit MIMO-OFDM Detection
In this study we analyze the convergence rate of EM for a class of approximate maximum-likelihood OMOD formulations, or, in a broader sense, a class of problems involving regression from quantized data.
SISAL Revisited
By establishing associations between the SISAL algorithm and a line-search-based proximal gradient method, we confirm that SISAL can indeed guarantee convergence to a stationary point.
Symbol-Level Precoding Through the Lens of Zero Forcing and Vector Perturbation
We examine how insights arising from this perturbed ZF and VP interpretations can be leveraged to i) substantially simplify the optimization of certain SLP design criteria, namely, total or peak power minimization subject to SEP quality guarantees; and ii) draw connections with some existing SLP designs.
One-Bit Symbol-Level Precoding for MU-MISO Downlink with Intelligent Reflecting Surface
This paper considers symbol-level precoding (SLP) for multiuser multi-input single-output (MISO) downlink transmission with the aid of intelligent reflecting surface (IRS).
Minimum Symbol-Error Probability Symbol-Level Precoding with Intelligent Reflecting Surface
Recently, the use of intelligent reflecting surface (IRS) has gained considerable attention in wireless communications.
