Optimized FPGA based continuous wavelet transform. (January 2016)

• Record Type: Journal Article
• Authors: Qassim, Yahya T.; Cutmore, Tim R.H.; Rowlands, David D.
• Is Part Of: Computers & electrical engineering. Volume 49(2016)
• Page Start: 84
• Page End: 94
• Publication Date: 2016-01
• Subjects: CWT -- EEG -- ERP -- FPGA -- Optimization; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2014.11.012
• Languages: English
• ISSNs: 0045-7906

Abstract

Graphical abstract: Highlights: We design highly optimized architecture for continuous wavelet transform in FPGA. Lookup tables are highly recommended in case of implementing complex algorithms. Zero-free wavelet function and scale reduction save extensive amount of block RAM. Spartan 3AN FPGA device is suitable for real time EEG analysis with the CWT. Abstract: A memory efficient field programmable gate array (FPGA) method is described that facilitates the processing of the continuous wavelet transform (CWT) arithmetic operations. The CWT computations were performed in Fourier space and implemented on FPGA following several optimization schemes. First, the adapted wavelet function was stored in a lookup table instead of computing the equation each time. Second, the utilization of FPGA memory was highly optimized by only storing the nonzero values of the wavelet function. This reduces 89% of the memory storage and allows fitting the entire design into the FPGA. Third, the design decreases the number of multiplications and shortens the time to produce the CWT coefficients. The proposed design was tested using EEG data and demonstrated to be suitable for extracting features from the event related potentials. Fourth, wavelet function scales were eliminated which saves further resources. The achieved computation speed allows for real time CWT application.