Abstract: A plurality of training inputs are selected, wherein each training input corresponds to a first possible output. The quality of each of the plurality of training inputs is characterized. A first training input is selected from the training inputs, where the first training input is of higher quality than a second training input of the training inputs. The neural network is trained with the higher-quality first training input prior to training with the second training input. A neuron may be added to the neural network in accordance with the first training input, wherein the neuron is associated with the first possible output.

Abstract: Disclosed is a ball support specially designed for golf practice, which mainly consists of a disk-like base and a ball holder associated with the base. The base is preferably made of rubber material and has a substantially conic top surface and a central through hole with downward expanded lower portion. The ball holder is also preferably made of rubber material and has a seat having a configuration corresponding to that of the central through hole of the base such that the ball holder may be fitly received in the base. The ball holder further has an inwardly curved and reduced waist portion and a top portion above the waist portion for holding a ball thereon. The top portion of the ball holder has a central semi-spherical recess and a further reduced hole formed on a bottom of the semi-spherical recess. With these arrangements, the club, the ball holder, and/or the disk-like base are not easily damaged due to incorrectly swung club during the practice.

Abstract: A classification method and apparatus for classifying an input into one of a plurality of possible outputs. Information representative of the input is compared to a neuron, where the neuron comprises a boundary defined by two or more neuron axes of different length. One of the possible outputs is then selected as corresponding to the input in accordance with that comparison. The invention is also a training method and apparatus for creating a new neuron or adjusting an existing neuron. A feature vector representative of a training input is generated, where the training input corresponds to one of a plurality of possible outputs. If no existing neuron corresponding to the training input encompasses the feature vector, then a new neuron is created, where the new neuron comprises a boundary defined by two or more neuron axes of different length.