Hi Yak, I posted some details of the patent under @uiux 's post....

Hi Yak,

I posted some details of the patent under @uiux 's post.

The patent, https://worldwide.espacenet.com/patent/search/family/074189798/publication/US2021027152A1?q=us20210027152 ,
describes the rank coding used in Akida, which is much more efficient than the known rate coding method.

[0054] Rate coding is shown in the top panel 310. The spikesreceived by two input synapses 320, 330 of a multitude of synapses are shownover one complete integration period labeled t1, in a plurality of integrationperiods. The first synapse received 25 spikes, while the second synapsereceived 27 spikes during this integration period. The sum of all synapses is52, which is the simulated membrane potential of the neuron. Subsequently anon-linear function such as Tanh(n) or a linear rectifier (ReLU) function isapplied to the simulated output value. The resulting output value istransmitted as a series of spikes to one or more synapses in the next neurallayer. The integration time is long to allow sufficient spikes to occurto receive a value.

In the lower left panel 33(4)0, rank coding is illustrated. The spikes received by four of a multitude of synapses is shown for six integration periods labeled t0 to t5. The integration time is short, and repeating spikes within each integration period are ignored. The integrated value for the first integration period is three, and four in the subsequent four integration periods. The last integration period has the value 2. These values (∑) are the simulated membrane potential of the neuron. If the simulated membrane potential reaches or exceeds a threshold value, a spike is transmitted to one or more synapses in the next neural layer. In the middle right hand panel 350, the integration method of a section of a neuron of a plurality of neurons in a conventional perceptron is shown. A collection of weight values labeled W11 to W95 are multiplied with input values I0 to I9.The resulting values are accumulated to form the neuron simulated membrane potential. Subsequently a non-linear function such as Tanh(n) or a linear rectifier (ReLU) function is applied to the simulated output value. The resulting output value is transmitted as an integer or floating-point value to one or more synapses in the next neural layer. In the lower right-hand panel 370, a conventional binary coding method is shown for reference. Binary coding schemes are widely used in conventional computer systems to encode characters and numbers. Boolean algebra is applied to compute with binary coded numbers and characters.