CORDIC algorithm and it’s applications in DSP

OBJECTIVE: The digital signal processing landscape has long been dominated by the microprocessors with enhancements such as single cycle multiply-accumulate instructions and special addressing modes. While these processors are low cost and offer extreme flexibility, they are often not fast enough for truly demanding DSP tasks. The advent of reconfigurable logic computers permits the higher speeds of dedicated hardware solutions at costs that are competitive with the traditional software approach. Unfortunately algorithms optimized for these microprocessors based systems do not map well into hardware. While hardware efficient solutions often exist, the dominance of the software systems has kept these solutions out of the spotlight. Among these hardware- efficient algorithms is a class of iterative solutions for trigonometric and other transcendental functions that use only shifts and adds to perform. The trigonometric functions are based on vector rotations, while other functions such as square root are implemented using an incremental expression of the desired function. The trigonometric algorithm is called CORDIC an acronym for Coordinate Rotation Digital Computer. The incremental functions are performed with a very simple extension to the hardware architecture and while not CORDIC in the strict sense, are often included because of the close similarity. The CORDIC algorithms generally produce one additional bit of accuracy for each iteration. DESCRIPTION: A detailed study on various modes of CORDIC algorithm is done. First of all a study is made how the CORDIC algorithm is derived from the general vector equation. Then a study is done regarding the various modes of the CORDIC algorithm and how it can be used to find the sine, cosine, tan and logarithm functions, its use in conversion of coordinate systems. An attempt is made to carry out a rigorous study of its use in DSP oriented applications AND how it has revolutionized the DSP scenario. Finally simulations are carried out using MATLAB to support the purpose of our study. RESULTS The results clearly bring out the advantage of using CORDIC algorithm. First of all the sine and cosine of any angle could be found out easily. Similar is the case of logarithm and hyperbolic functions. The simulation results prove the fact that the hardware complexity gets reduced by using the CORDIC algorithm. A large no of plots were obtained for different 7 functions. Finally the implementation in DCT was carried out and the results obtained were in line with those of the theoretical values. CONCLUSION The CORDIC algorithms presented in this paper are well known in the research and super computing circles. Here the basic CORDIC algorithm and a partial list of potential applications of potential applications of a CORDIC based processor array to digital signal processing is presented. The CORDIC based DCT architecture for low power design has been proposed. The proposed multiplierless CORDIC based DCT architecture produces high throughput and is easy to implementing VLSI. The proposed architecture reduced the input data range for the CORDIC processor by split and the no of compensation iterations in CORDIC based DCT computation by utilizing that most images have similar neighboring pixels. The project also shows that a tool is available for use in FPGA based computing machines, which are the likely basis for the next generation DSP systems

Arquitectura de Alto Rendimiento para el Cálculo de la DCT

En este trabajo se han revisado los principales métodos de cálculo de la Transformada Discreta del Coseno y sus implementaciones. A partir de esta información se ha propuesto una arquitectura de cálculo de alto rendimiento que pone en práctica técnicas de aritmética de computadores en el desarrollo de operadores para crear una estructura compacta que calcula la transformada a partir de su formulación directa. Se ha implementado y simulado el funcionamiento de la arquitectura propuesta en tarjetas reconfigurables para el Procesamiento de señales digitales, para evaluar su rendimiento en términos de área, retardo y potencia consumida. Además, se ha calculado su rendimiento con un modelo homogéneo e independiente de la tecnología de implementación con el propósito de comparar sus prestaciones con las de otras técnicas conocidas

Joint Optimization of Low-power DCT Architecture and Effcient Quantization Technique for Embedded Image Compression

International audienceThe Discrete Cosine Transform (DCT)-based image com- pression is widely used in today's communication systems. Signi cant research devoted to this domain has demonstrated that the optical com- pression methods can o er a higher speed but su er from bad image quality and a growing complexity. To meet the challenges of higher im- age quality and high speed processing, in this chapter, we present a joint system for DCT-based image compression by combining a VLSI archi- tecture of the DCT algorithm and an e cient quantization technique. Our approach is, rstly, based on a new granularity method in order to take advantage of the adjacent pixel correlation of the input blocks and to improve the visual quality of the reconstructed image. Second, a new architecture based on the Canonical Signed Digit and a novel Common Subexpression Elimination technique is proposed to replace the constant multipliers. Finally, a recon gurable quantization method is presented to e ectively save the computational complexity. Experimental results obtained with a prototype based on FPGA implementation and com- parisons with existing works corroborate the validity of the proposed optimizations in terms of power reduction, speed increase, silicon area saving and PSNR improvement

VLSI Implementation of a Cost-Efficient Loeffler-DCT Algorithm with Recursive CORDIC for DCT-Based Encoder

This paper presents a low-cost and high-quality; hardware-oriented; two-dimensional discrete cosine transform (2-D DCT) signal analyzer for image and video encoders. In order to reduce memory requirement and improve image quality; a novel Loeffler DCT based on a coordinate rotation digital computer (CORDIC) technique is proposed. In addition; the proposed algorithm is realized by a recursive CORDIC architecture instead of an unfolded CORDIC architecture with approximated scale factors. In the proposed design; a fully pipelined architecture is developed to efficiently increase operating frequency and throughput; and scale factors are implemented by using four hardware-sharing machines for complexity reduction. Thus; the computational complexity can be decreased significantly with only 0.01 dB loss deviated from the optimal image quality of the Loeffler DCT. Experimental results show that the proposed 2-D DCT spectral analyzer not only achieved a superior average peak signal–noise ratio (PSNR) compared to the previous CORDIC-DCT algorithms but also designed cost-efficient architecture for very large scale integration (VLSI) implementation. The proposed design was realized using a UMC 0.18-μm CMOS process with a synthesized gate count of 8.04 k and core area of 75,100 μm2. Its operating frequency was 100 MHz and power consumption was 4.17 mW. Moreover; this work had at least a 64.1% gate count reduction and saved at least 22.5% in power consumption compared to previous designs

Study of CORDIC based processing element for digital signal processing algorithms

There is a high demand for the efficient implementation of complex arithmetic operations in many Digital Signal Processing (DSP) algorithms. The COordinate Rotation DIgital Computer (CORDIC) algorithm is suitable to be implemented in DSP algorithms since its calculation for complex arithmetic is simple and elegant. Besides, since it avoids using multiplications, adopting the CORDIC algorithm can reduce the complexity. Here, in this project CORDIC based processing element for the construction of digital signal processing algorithms is implemented. This is a flexible device that can be used in the implementation of functions such as Singular Value Decomposition (SVD), Discrete Cosine Transform (DCT) as well as many other important functions. It uses a CORDIC module to perform arithmetic operations and the result is a flexible computational processing element (PE) for digital signal processing algorithms. To implement the CORDIC based architectures for functions like SVD and DCT, it is required to decompose their computations in terms of CORDIC operations. SVD is widely used in digital signal processing applications such as direction estimation, recursive least squares (RLS) filtering and system identification. Two different Jacobi-type methods for SVD parallel computation are usually considered, namely the Kogbetliantz (two-sided rotation) and the Hestenes (one- sided rotation) method. Kogbetliantz’s method has been considered, because it is suitable for mapping onto CORDIC array architecture and highly suitable for parallel computation. Here in its implementation, CORDIC algorithm provides the arithmetic units required in the processing elements as these enable the efficient implementation of plane rotation and phase computation. Many fundamental aspects of linear algebra rely on determining the rank of a matrix, making the SVD an important and widely used technique. DCT is one of the most widely used transform techniques in digital signal processing and it computation involves many multiplications and additions. The DCT based on CORDIC algorithm does not need multipliers. Moreover, it has regularity and simple architecture and it is used to compress a wide variety of images by transferring data into frequency domain. These digital signal-processing algorithms are used in many applications. The purpose of this thesis is to describe a solution in which a conventional CORDIC system is used to implement an SVD and DCT processing elements. The approach presented combines the low circuit complexity with high performance

Efficient and Accurate CORDIC Pipelined Architecture Chip Design Based on Binomial Approximation for Biped Robot

Recently, much research has focused on the design of biped robots with stable and smooth walking ability, identical to human beings, and thus, in the coming years, biped robots will accomplish rescue or exploration tasks in challenging environments. To achieve this goal, one of the important problems is to design a chip for real-time calculation of moving length and rotation angle of the biped robot. This paper presents an efficient and accurate coordinate rotation digital computer (CORDIC)-based efficient chip design to calculate the moving length and rotation angle for each step of the biped robot. In a previous work, the hardware cost of the accurate CORDIC-based algorithm of biped robots was primarily limited by the scale-factor architecture. To solve this problem, a binomial approximation was carefully employed for computing the scale-factor. In doing so, the CORDIC-based architecture can achieve similar accuracy but with fewer iterations, thus reducing hardware cost. Hence, incorporating CORDIC-based architecture with binomial approximation, pipelined architecture, and hardware sharing machines, this paper proposes a novel efficient and accurate CORDIC-based chip design by using an iterative pipelining architecture for biped robots. In this design, only low-complexity shift and add operators were used for realizing efficient hardware architecture and achieving the real-time computation of lengths and angles for biped robots. Compared with current designs, this work reduced hardware cost by 7.2%, decreased average errors by 94.5%, and improved average executing performance by 31.5%, when computing ten angles of biped robots

A low multiplicative complexity fast recursive DCT-2 algorithm

A fast Discrete Cosine Transform (DCT) algorithm is introduced that can be of particular interest in image processing. The main features of the algorithm are regularity of the graph and very low arithmetic complexity. The 16-point version of the algorithm requires only 32 multiplications and 81 additions. The computational core of the algorithm consists of only 17 nontrivial multiplications, the rest 15 are scaling factors that can be compensated in the post-processing. The derivation of the algorithm is based on the algebraic signal processing theory (ASP).Comment: 4 pages, 2 figure