Hi

A comment on very general theoretical level. I notice that the algorithms are written in the form of prevailing mainstream pure mathematics, containing trigonometric etc transcendental functions. The problem, and I think it is a deep one and even paradigmatic, is that computers don't do "actual infinities" of real numbers etc., but just finite notations for rational numbers such as 'floating points', p-adic 'quote notation' etc. This disparity between used mathematical language and its presuppositions, and what computers actually do, can easily lead to confusion e.g. when studying connections between neural networks and more general theories of cognition.

Rational and finitist theory of math, e.g. such as being developed by Norman J Wildberger, would be more consistent foundation for at least all computer oriented approaches, as well as more easy to communicate. Theoretical implications of such approach cannot be predicted, but they could be far reaching and radical. But in any case it seems very plausible that algorithms based on theory of math that is inherently purely computable - rational and finitist - could greatly enhance the machine computation efficiency and transparency.