Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Classification of Radio Signals Using Truncated Gaussian Discriminant
  Analysis of Convolutional Neural Network-Derived Features   To improve the utility and scalability of distributed radio frequency (RF)
sensor and communication networks, reduce the need for convolutional neural
network (CNN) retraining, and efficiently share learned information about
signals, we examined a supervised bootstrapping approach for RF modulation
classification. We show that CNN-bootstrapped features of new and existing
modulation classes can be considered as mixtures of truncated Gaussian
distributions, allowing for maximumlikelihood-based classification of new
classes without retraining the network. In this work, the authors observed
classification performance using maximum likelihood estimation of
CNNbootstrapped features to be comparable to that of a CNN trained on all
classes, even for those classes on which the bootstrapping CNN was not trained.
This performance was achieved while reducing the number of parameters needed
for new class definition from over 8 million to only 200. Furthermore, some
physical features of interest, not directly labeled during training, e.g.
signal-to-noise ratio (SNR), can be learned or estimated from these same
CNN-derived features. Finally, we show that SNR estimation accuracy is highest
when classification accuracy is lowest and therefore can be used to calibrate a
confidence in the classification.

28
The categories of this paper are: alg-geom
5
The categories of this paper are: gr-qc
21
The categories of this paper are: adap-org
31
The categories of this paper are: ao-sci
23
The categories of this paper are: solv-int
4
The categories of this paper are: cond-mat
15
The categories of this paper are: nucl-ex
29
The categories of this paper are: funct-an
25
The categories of this paper are: patt-sol
24
The categories of this paper are: dg-ga
37
The categories of this paper are: supr-con
1
The categories of this paper are: cs
17
The categories of this paper are: q-fin
30
The categories of this paper are: q-alg
35
The categories of this paper are: mtrl-th
9
The categories of this paper are: nlin