An information processing device includes: a processor that executes a process, the process including: controlling a recognition process that performs, with respect to input neuron data, a hierarchical neural network operation including a weighting operation using a parameter and that holds the neuron data and the parameter of each layer of the neural network in each of memory areas; and performing, in a learning process of learning the parameter of each layer of the neural network from an error that is obtained from a recognition result, regarding the layer in which the neuron data and the parameter are held in the memory areas, control of calculating an error of the neuron data after calculating an error of the parameter.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. An information processing device comprising: a processor that executes a process, the process comprising: controlling a recognition process that performs, with respect to input neuron data, a hierarchical neural network operation including a weighting operation using a parameter and that holds the neuron data and the parameter of each layer of the neural network in each of memory areas; and performing, in a learning process of learning the parameter of each layer of the neural network from an error that is obtained from a recognition result, regarding the layer in which the neuron data and the parameter are held in the memory areas, control of calculating an error of the neuron data after calculating an error of the parameter. 2. The information processing device according to claim 1, wherein, the performing performs, regarding the layer in which the neuron data and the parameter are held in the memory areas, control of, after calculating the error of the parameter and holding the calculated error in a new memory area, calculating the error of the neuron data and then overwriting and holding the error of the subject neuron data in the memory area in which the neuron data obtained from the recognition process is held. 3. The information processing device according to claim 1, wherein, the performing calculates, regarding the layer in which the neuron data and the parameter are held in the memory areas, the error of the parameter from the neuron data of the subject layer held at the time of the recognition process and the neuron data of the layer previous to the subject layer and calculates the error of the neuron data from the parameter of the subject layer and the neuron data of the layer previous to the subject layer. 4. The information processing device according to claim to 1, the process further comprising calculating the amount of memory used to store the error of the parameter of each layer of the neural network, wherein the performing performs control of reserving the memory area that is associated with the amount of memory used in the layer in which the amount of memory used is the greatest out of the calculated amount of memory used in each layer, regarding the layer in which the neuron data and the parameter are held in the memory areas, calculating, in the learning process, for each layer, the error of the parameter and then overwriting and holding the error of the subject parameter in the reserved memory area, calculating, in the learning process, for each layer, the error of the neuron data and then overwriting and holding the error of the subject neuron data in the memory area in which the neuron data obtained from the recognition process is held, and updating, by using the error of the parameter held in the reserved memory area, the parameter held at the time of the recognition process. 5. An information processing system comprising: a recognition control unit controls a recognition process that performs, with respect to input neuron data, a hierarchical neural network operation including a weighting operation using a parameter and that holds the neuron data and the parameter of each layer of the neural network in each of memory areas; and a learning control unit that performs, in a learning process of learning the parameter of each layer of the neural network from an error that is obtained from a recognition result by the recognition control unit, regarding the layer in which the neuron data and the parameter are held in the memory areas, control of calculating an error of the neuron data after calculating an error of the parameter. 6. A non-transitory computer-readable recording medium having stored therein a program that causes a computer to execute a process comprising: controlling a recognition process that performs, with respect to input neuron data, a hierarchical neural network operation including a weighting operation using a parameter and that holds the neuron data and the parameter of each layer of the neural network in each of memory areas; and performing, in a learning process of learning the parameter of each layer of the neural network from an error that is obtained from a recognition result, regarding the layer in which the neuron data and the parameter are held in the memory areas, control of calculating an error of the neuron data after calculating an error of the parameter.