Computing the discrete Fourier transform on FPGA based systolic arrays

While systolic array architectures have the potential to deliver tremendous performance, it is notoriously challenging to customize an efficient systolic array processor for a target application. Designing systolic arrays requires knowledge for both ...

Convolutional neural networks (CNNs) have been widely applied in many deep learning applications. In recent years, the FPGA implementation for CNNs has attracted much attention because of its high performance and energy efficiency. However, existing ...

The current trend back toward hardware intensive signal processing has uncovered a relative lack of understanding of hardware signal processing architectures. Many hardware efficient algorithms exist, but these are generally not well known due to the ...