Pattern Recognition as a Problem in Decision Theory and an Application to Speech Recognition

1963 ◽  
Vol MIL-7 (2 & 3) ◽  
pp. 186-189
Author(s):  
V. E. Sackschewsky ◽  
H. L. Oestreicher
Keyword(s):  
Pattern Recognition ◽  
Speech Recognition ◽  
Decision Theory

Research on Modulation Recognition Algorithm of Digital Communication Signal Based on Wavelet Denoising

2014 ◽  
Vol 608-609 ◽  
pp. 459-467 ◽  
Author(s):  
Xiao Yu Gu
Keyword(s):  
Pattern Recognition ◽  
Feature Extraction ◽  
Decision Theory ◽  
Recognition Rate ◽  
Recognition Algorithm ◽  
Modulation Recognition ◽  
The Core ◽  
Feature Parameters ◽  
Communication Signal ◽  
Modulation Signal

The paper researches a recognition algorithm of modulation signal and modulation modes. The modulation modes to be recognized include 2ASK, 2FSK, 2PSK, 4ASK, 4FSK and 4PSK modulation. There are two methods recognizing modulation modes of digital signal, method based on decision theory and pattern-recognition method based on feature extraction. The method based on decision theory is not suitable for recognition with multiple modulation modes. The core of pattern recognition based on feature extraction is selection of feature parameters. So the paper uses the feature parameters with simple calculation, easy to be implemented and high recognition rate as the core. The extraction of feature parameters is based on instant feature of modulation signal after Hilbert transformation.

ON THE USE OF THE MORPHIC GENERATOR GRAMMATICAL INFERENCE (MGGI) METHODOLOGY IN AUTOMATIC SPEECH RECOGNITION

1990 ◽  
Vol 04 (04) ◽  
pp. 667-685 ◽  
Author(s):  
PEDRO GARCÍA ◽  
ENCARNA SEGARRA ◽  
ENRIQUE VIDAL ◽  
ISABEL GALIANO
Keyword(s):  
Pattern Recognition ◽  
Speech Recognition ◽  
Automatic Speech Recognition ◽  
Regular Languages ◽  
Grammatical Inference ◽  
Real Problem ◽  
Syntactic Pattern Recognition ◽  
General Methodology ◽  
Syntactic Pattern

Recently, a new methodology, referred to as “Morphic Generator Grammatical Inference” (MGGI), has been introduced as a step towards a general methodology for the inference of regular languages. In this paper we consider the application of this methodology to a real problem of automatic speech recognition, thus allowing (and also requiring) the proposed problem to be properly formulated within the canonical framework of syntactic pattern recognition. The results show both the viability and appropriateness of the application of MGGI to the problem considered.

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