Multisignal Modulation Classification Using Sliding Window …
2022年4月15日 · Based on sliding window and deep learning (DL), this study proposes a multisignal frequency domain detection and recognition method. The frequency spectrum of the time-domain overlapping signal is obtained through the fast Fourier transform (FFT), and the frequency spectrum is segmented based on the signal energy detection method.
IR-Driven Multisignal Conditioning for Multiplex Detection: …
2025年1月3日 · The feasibility of the IR-driven multisignal conditioning sensor is confirmed by detecting coexistent antibiotics kanamycin (KANA) and neomycin (NEO) in complex real samples. The low-loss interface reconfiguration and rapid “four-to-one” multisignal modulation highlight a broad prospect for self-calibrating multiplex assay in the fields of ...
Multi-Signal Detection Framework: A Deep Learning Based Carrier ...
Multi-signal detection is aiming to jointly determine the existence of signals in a specific wideband, and estimate signal parameters such as the number of separable signals, center frequencies, and bandwidths. This is different from most spectrum sensing works, which only estimate signal “presence” or “absence”. 1.1. Related Works and Motivations.
Multisignal Analysis - MathWorks
Analyze multivariate signals using wavelet transforms and principal component analysis. Analyze, compress, and denoise multivariate correlated time series data. Approximate a multivariate signal using principal component analysis. How useful was this information?
Multi-Signal Classification Using Deep Learning and Sparse Arrays
2022年11月28日 · Abstract: In uncoordinated spectrum scenarios, such as shared spectrum, accurate spectral analysis is challenging if devices are interfering with one another. This paper examines wireless standard classification for spatially separated emitters that are interfering in time and frequency.
DeepMUSIC: Multiple Signal Classification via Deep Learning
2020年3月12日 · We design multiple deep convolutional neural networks (CNNs), each of which is dedicated to a subregion of the angular spectrum. Each CNN learns the MUltiple SIgnal Classification (MUSIC) spectra of the corresponding angular subregion. Hence, it constructs a nonlinear relationship between the received sensor data and the angular spectrum.
Multi-Signal Detection Framework: A Deep Learning Based …
2022年5月21日 · Multi-signal detection is of great significance in civil and military fields, such as cognitive radio (CR), spectrum monitoring, and signal reconnaissance, which refers to jointly detecting the presence of multiple signals in the observed frequency band, as well as estimating their carrier frequencies and bandwidths.
Multi-signal detection and parameter estimation fusion with …
2020年3月1日 · For the multi-signal case, one needs to not only determine the presence of signals or not, but also to estimate the number of signals and the corresponding parameters. In this paper, we focus on modeling and solving the multi …
PyQt5最全81 信号与槽之为类添加多个参数可选的信号_pyqt带多 …
2021年12月15日 · 本文详细介绍了如何在PyQt5中为类定义并使用带有多个可选参数的信号与槽。通过实例MultiSignal展示如何创建不同类型的信号，如无参、带整数、字符串、列表和字典，以及如何根据参数类型进行信号重载和连接槽函数。
Multisignal 1-D Wavelet Analysis - MathWorks
A 1-D multisignal is a set of 1-D signals of equal length stored as a matrix organized rowwise (or columnwise). This example shows how to analyze, denoise or compress a multisignal, and then to cluster different representations or simplified versions of the signals composing the multisignal.