By Y.T. Lo
Quantity 1: Antenna basics and Mathematical ideas opens with a dialogue of the basics and mathematical thoughts for any type of paintings with antennas, together with easy ideas, theorems, and formulation, and methods. DLC: Antennas (Electronics)
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Additional resources for Antenna Handbook - Applications
The probability of a spike, p (spike), can be simply obtained as the percentage of the spikes occurring during a large segment of the spike train such that the estimate is reliable, and the value is not very small. p (spike | angle) is the conditional probability density of the spike given the direction angle. For each neuron, the histogram of the spike-triggered angle can be drawn and normalized to approximate p (spike = 1, angle). In other words, only when there is a spike, the direction angle is counted for the histogram during the corresponding direction angle bin.
The electrical potentials superimpose as the sum of the individual potentials as they approach the threshold. Pulse densities are monotonically dependent on wave current densities. The range is bounded by threshold at the low end and refractoriness at the high end, with a near-linear small-signal range. This is similar to the sigmoidal curve in artiicial neural networks, with a major and signiicant difference: the nonlinearity is asymmetric with the maximal slope skewed to the right translating the neuron's excitatory nature.
The number in each box denotes the value of uj(k0) for j = 0, … , 7. to not exceed 1 sec because it has been reported that only the past neuronal activity up to 1 sec is correlated with the current behavior . In the following case examples, we select eight scales of binning starting at 5 up to 640 msec, with the dyadic scaling of 5, 10, 20, 40, 80, 160, 320, and 640 msec. With the selected scales, the HatWT is performed on an ensemble of BMI neuronal spike trains in the following way. We irst generate the basic bin count data with a 5-msec nonoverlapping window for every neuronal channel.