In recent years, the olfactory analogue technology based on the smell sensor array and pattern recognition becomes a research hot point in the world.

The structure activity relationship was studied by the pattern recognition method.

In this paper,the fundamental of predicting karst-fractured zones using both seismic attribute technique and pattern recognition method is introduced.

In order to improve recognition probability and decrease recognition time of the classifier of modulation recognition,and to make it adaptive,the self-organizing feature map neural network(SOM) was used as the classifier of modulation recognition,applying its property of self-organizing and adaptation to adapt automatically variety of the signal to noise ratio.

Digital modulation recognition has found important applications both in military and civil,while the feature extraction is the preliminary step for digital modulation recognition.

The modulation recognition technique of QAM signal by the constellation diagram is given in this paper.

Likelihood methods for PSK/QAM modulation classification;

Based on the communication signal modulation classification algorithm and software defined radio technology, this paper represents the signal processing framework which is applied in the implementation of the whole MC platform.

Modulation Classification (MC) and Blind Receiver Design are extremely important both in commercial (such as software defined radio) and military (such as and electronic warfare) communication systems.