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This paper combines a digital signal processor (DSP) and a field programmable gate array (FPGA) to realize the online empirical mode decomposition (EMD)-based signal processing system. The EMD algorithm is a novel signal analysis technique, decomposing signals into a series of intrinsic mode functions. First, the EMD algorithm is implemented in the DSP, named the EMD processor, which has the ability to eliminate noise from the original signal. Next, in order to process the online sequential signal, this paper proposes and implements pipeline and data transfer controllers in the FPGA, called the data processing flow processor. Then, the data processing flow processor coordinates the EMD processor, analog-to-digital converter, and digital-to-analog converter module boards. Finally, this paper presents a prototype of the online EMD-based electrocardiogram denoise system to verify the features of the proposed architecture. The emulations and experimental results demonstrate the effectiveness of the presented system as expected. [ABSTRACT FROM AUTHOR]

The ATLAS Hadronic Tile Calorimeter detector (TileCal) is an iron-scintillating tiles sampling calorimeter de- signed to operate at the Large Hadron Collider accelerator at CERN. The central element of the back-end system of the TileCal detector is a 9U VME Read-Out Driver (ROD) board. The operation of the TileCal calorimeter requires a total of 32 ROD boards. This paper summarizes the tests performed during the ROD production and the results obtained. Data processing is performed in the ROD by digital signal processors, whose operation is based on the use of online algorithms such as the optimal filtering algorithm for the signal amplitude, pedestal and time reconstruction and the online Muon tagging algorithm which identifies low transverse momentum muons. The initial performance of both algorithms run during commissioning is also presented in this paper. [ABSTRACT FROM AUTHOR]