Low precision neural networks using subband decomposition

An artificial neural network method including the steps of:

• receiving input data that defines a pattern to be recognized;
• decomposing the input data into a first subband and a second subband, wherein the first subband and the second subband include different characterizing features of the pattern in the input data;
• applying a first weight to the first subband and a second weight to the second subband, wherein the first weight is different from the second weight;
• and
• feeding the first subband and not the second subband into a first neural network and feeding the second subband and not the first subband into a second neural network, the first neural network and the second neural network being trained to recognize the pattern, wherein the first neural network is different from the second neural network.

A non-transitory, computer-readable medium comprising instructions that, when executed, are configured to cause processing circuitry of an artificial neural network system to

• receive input data that defines a pattern to be recognized;
• decompose the input data into a first subband and a second subband, wherein the first subband and the second subband include different characterizing features of the pattern in the input data;
• apply a first weight to the first subband and a second weight to the second subband, wherein the first weight is different from the second weight;
• and
• feed the first subband and not the second subband into a first neural network and feed the second subband and not the first subband into a second neural network, the first neural network and the second neural network being trained to recognize the pattern, wherein the first neural network is different from the second neural network.