Pattern discrimination method with a boosting approach using hierarchical neural trees

This paper proposes a new pattern classification method using probabilistic neural networks based on a boosting approach. In this method, a log-linearized Gaussian mixture network is used as a weak classifier. The method proposed automatically constructs a suitable classification network from given data. Validity of the proposed method is shown by discrimination results of artificial data and hand shape. The application is confirmed of the proposed method to human interface controlling of home electric appliances using hand shapes.