A neural network device includes a crossbar grid including first metal lines running in a first direction and second metal lines running transversely to the first metal lines and being electrically isolated from the first metal lines. An array of cross-over elements is included. Each cross-over element is connected between a first metal line and a second metal line. The cross-over elements each include a floating gate transistor device having a floating node. The floating node is configured to store a programmable weight value.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A neural network device, comprising: a crossbar grid including first metal lines running in a first direction and second metal lines running transversely to the first metal lines and being electrically isolated from the first metal lines; and an array of cross-over elements, each being connected between a first metal line and a second metal line, the cross-over element including at least one floating gate transistor device having a floating node, the floating node being configured to store a programmable weight value. 2. The neural network device, as recited in claim 1, further comprising: control circuitry to generate a set pulse sequence for setting the weight value on the floating node. 3. The neural network device, as recited in claim 1, further comprising: control circuitry to generate a reset pulse sequence for changing the weight value on the floating node. 4. The neural network device, as recited in claim 1, further comprising: control circuitry to generate a read pulse sequence for reading the weight value on the floating node. 5. The neural network device, as recited in claim 1, wherein the first metal lines include bitlines and the second metal lines include word lines. 6. The neural network device, as recited in claim 1, wherein the cross-over elements additionally include a logic device. 7. The neural network device, as recited in claim 1, wherein the cross-over elements additionally include one or more capacitors. 8. The neural network device, as recited in claim 1, wherein the at least one floating gate transistor device includes a gate structure having a first gate dielectric layer, the floating node, a second gate dielectric layer and a gate conductor. 9. The neural network device, as recited in claim 1, wherein the at least one floating gate transistor device includes an analog device. 10. A neural network device, comprising: a crossbar grid including first metal lines running in a first direction and second metal lines running transversely to the first metal lines and being electrically isolated from the first metal lines; an array of cross-over elements, each being connected between a first metal line and a second metal line, the cross-over elements including at least one floating gate transistor device having a floating node, the floating node being configured to store a programmable weight value; and control circuitry selectively coupled to the crossbar grid to generate and send pulse sequences for setting, resetting or reading the weight value to/from the floating node. 11. The neural network device, as recited in claim 10, wherein the first metal lines include bitlines and the second metal lines include word lines. 12. The neural network device, as recited in claim 10, wherein the cross-over elements additionally include a logic device. 13. The neural network device, as recited in claim 10, wherein the cross-over elements additionally include one or more capacitors. 14. The neural network device, as recited in claim 10, wherein the at least one floating gate transistor device includes a gate structure having a first gate dielectric layer, the floating node, a second gate dielectric layer and a gate conductor. 15. The neural network device, as recited in claim 10, wherein the at least one floating gate transistor device includes an analog device. 16. A method for programming a neural network device, comprising: selectively generating pulses on a crossbar grid including first metal lines running in a first direction and second metal lines running transversely to the first metal lines and being electrically isolated from the first metal lines; programming weight values in cross-over elements electrically connected between the first metal lines and the second metal lines in the cross bar grid by storing charge in a floating node of a floating gate transistor device of the cross-over elements; and computing an output using an input modified by the weight values. 17. The method, as recited in claim 15, wherein the cross-over elements additionally include a logic device. 18. The method, as recited in claim 15, wherein the cross-over elements additionally include one or more capacitors. 19. The method, as recited in claim 15, wherein programming the weight values in the cross-over elements includes setting the weight values by concurrent pulses on a first metal line and a second metal line for each floating gate transistor device to be programmed. 20. The method, as recited in claim 15, further comprising reading out the weight values on a second metal line in accordance with a pulse on a first metal line.