1 天前 - … modulation classification, crucial for effective spectrum monitoring and management.
Presently, Artificial Neural Network (ANN)-based deep learning … in the deep learning …

4 天前 - … However, deep learning-based AMC models are … and uncovering modern modulation
classifiers’ vulnerability to … the limitations and vulnerabilities of deep learning-based AMC …

8 天前 - … deep learning with high-spatial-resolution signals, such as EROS, can be successfully
applied to single-trial classifications… light (830 nm) modulated at 110 MHz over frontal …

9 天前 - … deep learning regression to overcome the drawback of the estimation accuracy of
classification … estimator from BPSK modulation to high-order modulation in complex channel. …

9 天前 - … signal parameter estimation methods, a parameter modulation method for multi-…
principle and deep learning is proposed. Firstly, classify and introduce the modulation methods, …

9 天前 - … using radar point cloud followed by deep learning model. Similarly, sleep posture
… a deep learning framework which can learn features from raw point cloud images to classify …

10 天前 - … classify intricate data structures. This study delves into the critical role of automatic
modulation classification … Neural Networks (CNN) as a deep learning approach. In this study, …

11 天前 - … Deep learning technology has demonstrated significant advantages in the field of
AMC, … and classifying modulation signal features. However, existing deep learning models …

14 天前 - … Despite the successful implementation of deep-learning algorithms, challenges
in … -modulated sinusoidal waves; and b) non-VIV datasets using generative deep-learning …

14 天前 - … Second, this research proves the use of CFs combined with deep learning (DL) for
a novel approach to emitter association by using channel identification. Finally, this research …