با عرض سلام مي خواهيم مقاله كنفرانسي با عنوان زير بنويسيم


Complex Sig: Complex deep model for signal classification

Abstract: The ability to classify signals is an important task that provides the opportunity for many different applications. In the early research for signal classification, they had to
decompose the signal using FT (Fourier transform), SIFT, MFCC or other manual methods using statistical modulation features, then classify these signals by a traditional machine learning approach. In the last few years, the process of learning deep models that lead to the automatic extraction of features has positively affected classification. Different deep-learning models with di erent depths have been proposed in the literature.
This article proposes different approaches to classify signals in different SNR conditions. ResNet-based approaches perform well for high SNRs but poorly when dealing with low SNRs. Therefore, TRansforme-based approaches were proposed for classification, reaching an average accuracy of 0.7056 in low SNR and an average of 0.9089 in high SNR.

نتايج اوليه خوب بوده و قابل مقايسه با ساير مقالات تو اين حوزه ميباشد. نياز به ٢ يا سه نفر داريم كه مشاركت كنند.
Price:
2: 300$
3:200$
4:100$

@Raminmousa
@paper4money
@Machine_learn