A calculator based on a spiking neural network, the network comprising layers of neurons, the inputs and outputs of each neuron being coded by spikes, the input spikes being received in sequence at the input of a neuron, each neuron of the network comprising a receptive field comprising at least one synapse, each synapse being associated with a synapse address, the calculator being configured to compute, for each layer of neurons, the output value of each neuron in response to at least one input spike, the network further comprising at least one maximum pooling layer, each pooling layer comprising maximum pooling neurons, each maximum pooling neuron being able to deliver an output spike in response to the reception of an input spike on the most active synapse of its receptive field, characterised in that the calculator comprises a device for activating the neurons of the maximum pooling layer and in that , in response to an input spike received by a neuron of the maximum pooling layer, the device is configured to receive the address of the synapse associated with said received input spike, called activated synapse address, the device comprising an address comparator configured to compare the address of the activated synapse with a set of reference addresses, comprising at least one reference address, each reference address being associated with a hardness value and with a pooling neuron; the device being configured to activate a neuron of the maximum pooling layer if the address of the activated synapse is equal to one of the reference addresses and the hardness value associated with this reference address has the highest value from among the hardness values associated with the other reference addresses of said set, the device being configured to set a reference address to the value of said activated synapse address, if said reference address is different from said activated synapse address and if the hardness value is less than or equal to zero, the device being further configured to deliver an output spike value with the value one, in association with said reference address and to set the hardness value associated with the reference address to a predefined initialisation value. the network further comprising at least one maximum pooling layer, each pooling layer comprising maximum pooling neurons, each maximum pooling neuron being able to deliver an output spike in response to the reception of an input spike on the most active synapse of its receptive field, characterised in that the calculator comprises a device for activating the neurons of the maximum pooling layer and in that , in response to an input spike received by a neuron of the maximum pooling layer, the device is configured to receive the address of the synapse associated with said received input spike, called activated synapse address, the device comprising an address comparator configured to compare the address of the activated synapse with a set of reference addresses, comprising at least one reference address, each reference address being associated with a hardness value and with a pooling neuron; the device being configured to activate a neuron of the maximum pooling layer if the address of the activated synapse is equal to one of the reference addresses and the hardness value associated with this reference address has the highest value from among the hardness values associated with the other reference addresses of said set, the device being configured to set a reference address to the value of said activated synapse address, if said reference address is different from said activated synapse address and if the hardness value is less than or equal to zero, the device being further configured to deliver an output spike value with the value one, in association with said reference address and to set the hardness value associated with the reference address to a predefined initialisation value. <EOS>