Title :
Daubechies-4 wavelets system-on-chip for classifications of mixed-chemical
Author :
Abdel-Aty-Zohdy, Hoda S. ; Roth, Stefan ; Mebrahtu, Ephram
Author_Institution :
Dept. of Electr. & Comput. Eng., Oakland Univ., Rochester, MI, USA
Abstract :
Wavelet transforms are favorably used for compressing and filtering complex signals from chemical sensors for classifications. The Daubechies 4 (D4) transform is used and found to be more accurate especially with chemical mixtures, fairly simple to implement, and effective at pre-processing data from 32 sensors. The resulting output of this system is sent to a Spiking Neural Network processing chip for chemical classification. The system features a SPI bus for data input and output. It accepts a 32 bit fixed point value inputs for faster processing using bit shifts and adds to implement multiplication. The system is designed to be modular and capable of being used on other potential applications. Experimental measurements of mixed gases, including IEDs, are presented. This paper presents the design evaluated on a VHDL platform, to be implemented on a Si chip for fabrication through MOSIS 0.5 um CMOS technology. D4 has more capability than Haar transform, especially with gas mixtures such as 0.1% of TATP/HMTD in Acetonitrile. This high precision system design occupies a silicon chip area of less than 2 mm2. Experimental results are presented with good sensitivity, stability, and tolerance.
Keywords :
CMOS integrated circuits; chemical engineering computing; chemical sensors; computerised instrumentation; data compression; elemental semiconductors; filtering theory; hardware description languages; neural chips; signal classification; silicon; system-on-chip; wavelet transforms; D4 transform; Daubechies-4 wavelets system-on-chip; Haar transform; IEDs; MOSIS CMOS technology; SPI bus; Si; TAT-HMTD; VHDL platform; acetonitrile; bit shifts; chemical sensors; complex signal filtering; fixed point value inputs; gas mixtures; high precision system design; mixed-chemical classifications; size 0.5 mum; spiking neural network processing chip; wavelet transforms; word length 32 bit;
Conference_Titel :
Circuits and Systems (MWSCAS), 2013 IEEE 56th International Midwest Symposium on
Conference_Location :
Columbus, OH
DOI :
10.1109/MWSCAS.2013.6674724