Assume we use single fingertip to touch one object multiple times. For simplicity, a 2D case of touching concave polygon with a foamy circle. Isn’t it very difficult to generate good location signal based only on skin mapping, movement around complex polygon and accumulating on output layer? Instead, location signal may be retrieved from memory about previously touched polygon. Each touch is first transformed through such memory, and then final location signal is accumulated. In my opinion, location signal somehow must be accumulated too, not only final output is accumulated over time. Also, weak signal must have ability to perform drastic change in location signal (“rotate” it, “scale”, re-use previous wrongly classified features)
Here is an example explaining this problem: we have two concave polygons (A) and (B), with very different shape. But there is small area on polygon(B), let’s say 5%, which is exact copy of (A) polygon’s shape. Assume we touch polygon (B) 1000 times only in this 5% area, output layer will accumulate some outputs. Because touched area is exact copy, it is not possible to distinguish between (A) and (B). Let’s then do one final single touch in remaining 95% area. Because (A) and (B) have very different shape, output layer must somehow change to one or another object, but it seems almost impossible, because we only have one single “weak” touch against previous 1000 touches + locations. How this problem is solved using current model? I think one explanation may be that there are a lot of columns, so this final touch still gets through, but it still gives me feeling that it will not work so good, because previous 1000 signals had this advantage too.