Title :
An Analog-Digital Neural Processor for Integrated Sensor Conditioning
Author :
Medrano, N. ; Sanz, M.T. ; Martínez, P.A. ; Celma, S. ; Zatorre, G.
Author_Institution :
Univ. de Zaragoza, Zaragoza
Abstract :
In this work a CMOS neural processor is presented. Based on a mixed analog-digital architecture, the system processes data in analog current mode, using digital registers to store weights safely. The proposed processor consists of two main blocks: A mixed-signal four-quadrant multiplier and a class AB current conveyor that implements the non-linear output function. Achieved from the circuit-level simulation, the neuron system-level model is used to study the application of this architecture to tackle linearization of a magnetoresistive sensor. Simulation results show the efficiency of the new implementation.
Keywords :
CMOS integrated circuits; magnetic sensors; magnetoresistive devices; mixed analogue-digital integrated circuits; neural chips; CMOS neural processor; analog current mode; analog-digital neural processor; digital registers; integrated sensor conditioning; magnetoresistive sensor; mixed-signal four-quadrant multiplier; neuron system-level model; Analog-digital conversion; Artificial neural networks; CMOS process; Circuit simulation; Electronic circuits; Energy consumption; Giant magnetoresistance; Inverters; Magnetic sensors; Neurons;
Conference_Titel :
Electronics, Circuits and Systems, 2006. ICECS '06. 13th IEEE International Conference on
Conference_Location :
Nice
Print_ISBN :
1-4244-0395-2
Electronic_ISBN :
1-4244-0395-2
DOI :
10.1109/ICECS.2006.379941
