Abstract: A neural processor apparatus implements a neural network at a low cost and with high efficiency by simultaneously processing a plurality of neurons using the same synaptic inputs. Weight data is sequentially accessed from an external weight RAM memory to minimize space on the IC. The input data and weight data may be configured as either a single, high-resolution input or a plurality of inputs having a lower resolution, whereby the plurality of inputs are processed simultaneously. A dynamic approximation method is implemented using a minimal amount of circuitry to provide high-resolution transformations in accordance with the transfer function of a given neuron model. The neural processor apparatus may be used to implement an entire neural network, or may be implemented using a plurality of devices, each device implementing a predetermined number of neural layers.