Hardware Neural Network

I'm sketchy on the details but I believe there are dedicated ANN devices available which could be an interesting diversion. Also I'd bet that someone has produced something in an FPGA that might be relevent.

Yes they have. The parallelism of the FPGA would probably make for a much faster solution too. However, a lot of your design decisions must be dictated by your application - there are a lot of ANN implementations out there and they are not necessarily all heavy on floating point.

Unless you really need the dynamic range of float, you should stick with integers. Consider that a 32 bit integer has a range of 10^9

Rene

Peter Meijer has an interesting page.

Also some other information.

There is a data sheet in amongst that lot.

Thanks for the hint, maybe I can "translate" the sigmoid in an 8-bit table and use it for setting the heights. This (if right) will avoid me the use of a 32-bit architecture. I'll think about it, thank you.

testo tra virgolette -

Thanks for the links, I'll have a look

daniele

I'm not so familiar with FPGA, but I will have a look at them thank you,

daniele

There are lots of tricks for implementing the sigmoid including luts, and luts with interpolation between lut entries taylor series approx, CORDIC approximations.

take a look at a computer arithmetic book and search on IEEE xplore you will find TONS of hardware implementations of NNs with all sorts of tricks to implement them with limited resources.