Elements of information theory
Elements of information theory
Independent component analysis, a new concept?
Signal Processing - Special issue on higher order statistics
A fast fixed-point algorithm for independent component analysis
Neural Computation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pilchard A Reconfigurable Computing Platform with Memory Slot Interface
FCCM '01 Proceedings of the the 9th Annual IEEE Symposium on Field-Programmable Custom Computing Machines
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A run-time reconfigurable field programmable gate array (FPGA) system is presented for the implementation of the parallel independent component analysis (ICA) algorithm. In this work, we investigate design challenges caused by the capacity constraints of single FPGA. Using the reconfigurability of FPGA, we show how to manipulate the FPGA-based system and execute processes for the parallel ICA (pICA) algorithm. During the implementation procedure, pICA is first partitioned into three temporally independent function blocks, each of which is synthesized by using several ICA-related reconfigurable components (RCs) that are developed for reuse and retargeting purposes. All blocks are then integrated into a design and development environment for performing tasks such as FPGA optimization, placement, and routing. With partitioning and reconfiguration, the proposed reconfigurable FPGA system overcomes the capacity constraints for the pICA implementation on embedded systems. We demonstrate the effectiveness of this implementation on real images with large throughput for dimensionality reduction in hyperspectral image (HSI) analysis.