Introduction to engineering through instruction on basic concepts of engineering. Prerequisite: MATH 200; and one of EGRE 101 or EGRB 102 or both EGMN 103 and EGMN 190, as applicable per department, all with minimum grades of C. An introduction to electrical circuit theory and its application to practical direct and alternating current circuits.
Course open to first-year students majoring in electrical or computer engineering. The laboratory exercises will serve to train students in the art of designing a circuit to perform specific tasks and to conform to specific design parameters.
To achieve the highest possible reliability in the detection of the type of modulation, it is proposed in accordance with the invention that the transformations are selected which, in the state diagram, transform the states which are symmetric with respect to the origin of the complex plane into a lower number of states which are asymmetric to the origin, that from the information signal and, respectively, the intermediate signals, the in each case associated power density spectra are generated which are examined for the existence of lines, and the number, frequency and amplitude of which are determined and forwarded to a classifier which determines from these the type of modulation.
EUROPEAN JOURNAL DEVOTED TO THE METHODS AND APPLICATIONS OF SIGNAL PROCESSING Bd.
Only the most well-known features and classifiers are considered, categorized, and defined.
The features include instantaneous time domain (ITD) parameters, Fourier transform (FT), wavelet transform (WT), higher order moments (HOM) to name a few.
GADBOIS: 'Indentification of the modulation type of a signal.'SIGNAL PROCESSING. EUROPEAN JOURNAL DEVOTED TO THE METHODS AND APPLICATIONS OF SIGNAL PROCESSING Bd.
ABSTRACT: This paper presents a method for the automatic classification of digital modulations without a priori knowledge of the signal parameters.
In order to design a flexible measurement instrument for digital telecommunication signals, a method has been proposed in a precedent paper.
In particular it has been validated in presence of additive white Gaussian noise, colored noise and multipath fading showing good classification percentages, also in very noisy environments.
ABSTRACT: This paper presents an overview of feature-based (FB) methods developed for Automatic classification of digital modulations.