Incremental and Transitive Discrete Rotations

A discrete rotation algorithm can be apprehended as a parametric application $f\_\alpha$ from \ZZ[i] to \ZZ[i], whose resulting permutation ``looks like'' the map induced by an Euclidean rotation. For this kind of algorithm, to be incremental means to compute successively all the intermediate rotate d copies of an image for angles in-between 0 and a destination angle. The di scretized rotation consists in the composition of an Euclidean rotation with a discretization; the aim of this article is to describe an algorithm whic h computes incrementally a discretized rotation. The suggested method uses o nly integer arithmetic and does not compute any sine nor any cosine. More pr ecisely, its design relies on the analysis of the discretized rotation as a step function: the precise description of the discontinuities turns to be th e key ingredient that will make the resulting procedure optimally fast and e xact. A complete description of the incremental rotation process is provided, also this result may be useful in the specification of a consistent set of defin itions for discrete geometry

Steerable Discrete Fourier Transform

Directional transforms have recently raised a lot of interest thanks to their numerous applications in signal compression and analysis. In this letter, we introduce a generalization of the discrete Fourier transform, called steerable DFT (SDFT). Since the DFT is used in numerous fields, it may be of interest in a wide range of applications. Moreover, we also show that the SDFT is highly related to other well-known transforms, such as the Fourier sine and cosine transforms and the Hilbert transforms

Identifying an Experimental Two-State Hamiltonian to Arbitrary Accuracy

Precision control of a quantum system requires accurate determination of the effective system Hamiltonian. We develop a method for estimating the Hamiltonian parameters for some unknown two-state system and providing uncertainty bounds on these parameters. This method requires only one measurement basis and the ability to initialise the system in some arbitrary state which is not an eigenstate of the Hamiltonian in question. The scaling of the uncertainty is studied for large numbers of measurements and found to be proportional to one on the square-root of the number of measurements.Comment: Minor corrections, Accepted for publication in Physical Review

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

Algebraic Signal Processing Theory: Cooley-Tukey Type Algorithms for DCTs and DSTs

This paper presents a systematic methodology based on the algebraic theory of signal processing to classify and derive fast algorithms for linear transforms. Instead of manipulating the entries of transform matrices, our approach derives the algorithms by stepwise decomposition of the associated signal models, or polynomial algebras. This decomposition is based on two generic methods or algebraic principles that generalize the well-known Cooley-Tukey FFT and make the algorithms' derivations concise and transparent. Application to the 16 discrete cosine and sine transforms yields a large class of fast algorithms, many of which have not been found before.Comment: 31 pages, more information at http://www.ece.cmu.edu/~smar

New virtually scaling free adaptive CORDIC rotator

In this article we propose a novel CORDIC rotator algorithm that eliminates the problems of scale factor compensation and limited range of convergence associated with the classical CORDIC algorithm. In our scheme, depending on the target angle or the initial coordinate of the vector, a scaling by 1 or 1/?2 is needed that can be realised with minimal hardware. The proposed CORDIC rotator adaptively selects appropriate iteration steps and converges to the final result by executing 50% less number of iterations on an average compared to that required for the classical CORDIC. Unlike classical CORDIC, the final value of the scale factor is completely independent of number of executed iterations. Based on the proposed algorithm, a 16-bit pipelined CORDIC rotator implementation has been described. The silicon area of the fabricated pipelined CORDIC rotator core is 2.73 mm2. This is equivalent to 38 k inverter gates in IHP in-house 0.25 ?m BiCMOS technology. The average dynamic power consumption of the fabricated CORDIC rotator is 17 mW @ 2.5 V supply and 20Msps throughput. Currently, this CORDIC rotator is used as a part of the baseband processor for a project that aims to design a single-chip wireless modem compliant with IEEE 802.11a and Hiperlan/2