This can be done. Simply look at the various implementation methodologies and compare with FPGA approach. The one that offers a lower cost, time to market and performance efficiency should take precedence. GNG on FPGA is possible!

Thanks. but I want to know why no one did not use it? is the complexity high or other reasons? I am not very familiar with them.

FPGAs are quiet complex because of its numerous gate arrays. Again, Verilog/VHDL implementation requires lots of understanding on design synthesis, routing and fitting.

But can effective if you can realize a functional design with it Ok. FPGAs are good for complex digital systems

Thanks. Are you familiar with Growing Neural gas(GNG)?I want to know just for this case.

Neural gas is an AI network, inspired by the self-organizing map (SOM). This concept was introduced by Thomas Martinetz and Klaus Schulten about 27years ago . GNG  is a simple algorithm for finding optimal data representations based on feature vectors. The algorithm is refereed as neural gas because of the dynamics of the feature vectors during the adaptation process, which distribute themselves like a gas within the data space. It is applied where data compression or vector quantization is an issue, for example speech recognition, image processing, and even in pattern recognition. it can be used as a better option to the k-means clustering.

Actually, you can implement GNG in either of the listed applications using FPGAs.

thanks a lot

You are welcome.