Efficient signal processing using syntactic pattern recognition methods

This paper presents an optimal architecture for hardware implementation of Context-Free Grammar (CFG) parsers, which can be used to accelerate the performance of applications where response to real time signal processing is a crucial aspect, such as Electrocardiogram (ECG) analysis. Our architecture increases the performance by a factor of approximately two orders of magnitude compared to the pure software implementation, depending on the CFG. This speed up derives mainly from the hardware nature of the implementation, the innovative combinatorial nature of the circuit that implements the fundamental operation of the parsing algorithm and the underlying data representation. We further propose an automated synthesis tool that, given the specification of an arbitrary CFG and using the aforementioned hardware architecture in a template form, generates the HDL (Hardware Design Language) synthesizable source code of the hardware parser for the given grammar. The proposed architecture may be used for real time applications, e.g. natural languages interfaces. The generated source has been simulated for validation, synthesized and tested on a Xilinx FPGA (Field Programmable Gate Array) board.