A joint numerical representation based on both Gaussian and Eisenstein integers is proposed. This Gauss-Eisenstein representation maps complex numbers into four-tuples of integers with arbitrarily high precision. The representation furnishes the computation of the 3-, 6-, and 12-point discrete Fourier transform (DFT) at any desired accuracy. The associated fast algorithms based on the Gauss-Eisenstein integers are error-free up to the final reconstruction step, which can be realized in hardware as a multiplierless implementation. The introduced methods are compared with competing algorithms in terms of arithmetic complexity. We propose three FRS architectures based on the following methods: Dempster-McLeod representation, expansion factor, and addition aware quantization. The Gauss-Eisenstein 12-point DFT is physically realized on a Xilinx Virtex 6 FPGA device with maximum clock frequency of 302 MHz for the expansion factor FRS with real-time throughput of 3:62 × 109 coefficients/s. The FPGA verified digital designs were synthesized, mapped, placed and finally routed for 0:18mm CMOS technology assuming a 1.8 V DC supply employing Austria Micro Systems (AMS) standard-cell library (hitkit version 4.11). The routed ASIC is predicted to operate at a maximum frequency of 505 MHz for the expansion factor FRS with potential real-time throughput of 6:06 × 109coefficients/s.

The discrete cosine transform (DCT) is a widely-used and important signal processing tool employed in a plethora of applications. Typical fast algorithms for nearly-exact computation of DCT require floating point arithmetic, are multiplier intensive, and accumulate round-off errors. Recently proposed fast algorithm arithmetic cosine transform (ACT) calculates the DCT exactly using only additions and integer constant multiplications, with very low area complexity, for null mean input sequences. The ACT can also be computed non-exactly for any input sequence, with low area complexity and low power consumption, utilizing the novel architecture described. However, as a trade-off, the ACT algorithm requires 10 non-uniformly sampled data points to calculate the eight-point DCT. This requirement can easily be satisfied for applications dealing with spatial signals such as image sensors and biomedical sensor arrays, by placing sensor elements in a non-uniform grid. In this work, a hardware architecture for the computation of the null mean ACT is proposed, followed by a novel architectures that extend the ACT for non-null mean signals. All circuits are physically implemented and tested using the Xilinx XC6VLX240T FPGA device and synthesized for 45 nm TSMC standard-cell library for performance assessment.

An area efficient row-parallel architecture is proposed for the real-time implementation of bivariate algebraic integer (AI) encoded 2-D discrete cosine transform (DCT) for image and video processing. The proposed architecture computes 8 × 8 2-D DCT transform based on the Arai DCT algorithm. An improved fast algorithm for AI-based 1-D DCT computation is proposed along with a single channel 2-D DCT architecture. The design improves on the four-channel AI DCT architecture that was published recently by reducing the number of integer channels to one and the number of eight-point 1-D DCT cores from five down to two. The architecture offers exact computation of 8 × 8 blocks of the 2-D DCT coefficients up to the FRS, which converts the coefficients from the AI representation to fixed-point format using the method of expansion factors. Prototype circuits corresponding to FRS blocks based on two expansion factors are realized, tested, and verified on FPGA-chip, using a Xilinx Virtex-6 XC6VLX240T device. Post place-and-route results show a 20% reduction in terms of area compared to the 2-D DCT architecture requiring five 1-D AI cores. The area-time and area-time2complexity metrics are also reduced by 23% and 22% respectively for designs with eight-bit input word length. The digital realizations are simulated up to place and route for ASICs using 45 nm CMOS standard cells. The maximum estimated clock rate is 951 MHz for the CMOS realizations indicating 7.608·109pixels/s and a 8 × 8 block rate of 118.875 MHz.

An algebraic integer (AI)-based time-multiplexed row-parallel architecture and two final reconstruction step (FRS) algorithms are proposed for the implementation of bivariate AI encoded 2-D discrete cosine transform (DCT). The architecture directly realizes an error-free 2-D DCT without using FRSs between row-column transforms, leading to an 8 × 8 2-D DCT that is entirely free of quantization errors in AI basis. As a result, the user-selectable accuracy for each of the coefficients in the FRS facilitates each of the 64 coefficients to have its precision set independently of others, avoiding the leakage of quantization noise between channels as is the case for published DCT designs. The proposed FRS uses two approaches based on: 1) optimized Dempster-Macleod multipliers, and 2) expansion factor scaling. This architecture enables low-noise high-dynamic range applications in digital video processing that requires full control of the finite-precision computation of the 2-D DCT. The proposed architectures and FRS techniques are experimentally verified and validated using hardware implementations that are physically realized and verified on field-programmable gate array (FPGA) chip. Six designs, for 4-bit and 8-bit input word sizes, using the two proposed FRS schemes, have been designed, simulated, physically implemented, and measured. The maximum clock rate and block rate achieved among 8-bit input designs are 307.787 MHz and 38.47 MHz, respectively, implying a pixel rate of 8 × 307.787≈2.462 GHz if eventually embedded in a real- time video-processing system. The equivalent frame rate is about 1187.35Hz for the image size of 1920 × 1080. All implementations are functional on a Xilinx Virtex-6 XC6VLX240T FPGA device.

This paper investigates the potential of emerging asynchronous quasi delay insensitive (a-QDI) logic devices for the realization of high-speed low-power 2D infinite impulse response digital beam filters. Recently proposed raster-scanned hardware architectures based on direct-form I and wave-digital realization are extended to clock-free asynchronous logic using state-of-the-art asynchronous field programmable gate arrays from Achronix Semiconductor. For the specific class of 2D IIR beam filters based on raster-scanned hardware, it is shown using extensive experimental work that direct-form I architectures greatly benefit from the adoption of a-QDI logic over standard clocked (synchronous) digital circuits while wave-digital filters show no difference in performance. To the author's knowledge, the proposed 2D IIR hardware circuits are currently the only available realization of 2D IIR filters in the literature based on the new clock-free a-QDI paradigm.