A Demonstration of the Use of Walsh Functions for Multiplexed Imaging
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Binary Polynomial Transforms for Nonlinear Signal Processing
BINARY POLYNOMIAL TRANSFORMS FOR NONLINEAR SIGNAL PROCESSING Jaakko Astola, Karen Egiazarian, Rugen oktern SOS Agaian Signal Processing Laboratory Electrical Engineering Department Tampere University of Technology University of Texas at San Antonio Tampere, FINLAND San Antonio, Texas, USA ABSTRACT ing computers or systems suitable for simultaneous arith- metical or logical operations. In this paper we introduce parametric binary Rademacher functions of two types. Based on them using different kinds 2. BINARY POLYNOMIAL FUNCTIONS AND of arithmetical and logical operations we generate a set of MATRICES binary polynomial transforms (BPT). Some applications of BPT in nonlinear filtering and in compression of binary 2.1. Rademacher Functions and Matrices images are presented. Let a and b be arbitrary integers. We form the classes r,(t,a, b) and s,(t,a, b) of real periodic functions in the 1. INTRODUCTION following way. Let Spectral analysis is a powerful tool in communication, sig- ro(t.a,b) E so(t,a, b) E 1, (1) nal/ image processing and applied mathematics and there are many reasons behind the usefulness of spectral analysis. First, in many applications it is convenient to transform a a, fortEU~~ol[$,fk++i), problem into another, easier problem; the spectral domain rn+l (t, a, b) = is essentially a steady-state viewpoint; this not only gives b, for t E U~~ol[ $t + 5&l *).2 insight for analysis but also for design. Second, and more (2) important: the spectral approach allows us to treat entire and classes of signals which have similar properties in the spec- tral domain; it has excellent properties such as fast algo- a: for t E LO,&I, n = 0, 1,2, . -
Walsh-Like Functions and Their Relations
WaIsh-like functions and their relations B.J. Falkowski S.Rahardja Indexing terms: Discrete transforms, Walshfunctions, Haar functions form except that the absolute value of the output is Abstract: A new discrete transform, the ‘Haar- taken before applying to the next stage. However, the Walsh transform’, has been introduced. Similar to rapid transform is nonorthogonal and does not have an well known Walsh and non-normalised Haar inverse. Another modified transform is based on a transforms, the new transform assumes only +1 hybrid version of the Haar and Walsh transforms [2, and -1 values, hence it is a Walsh-like function 111. This transform is derived from different linear and can be used in different applications of combinations of the basis Haar functions with an digital signal and image processing. In particular, appropriate scaling factor. Such a combinatioii of basis it is extremely well suited to the processing of functions have been found advantageous for feature two-valued binary logic signals. Besides being a selection and pattern recognition. The rationalised ver- discrete transform on its own, the proposed sion of this transform has also been introduced [12]. transform can also convert Haar and Walsh Another family of orthogonal functions related to the spectra uniquely between themselves. Besides the Walsh and Haar functions has been introduced [13-15]1. fast algorithm that can be implemented in the They are called bridge functions and can be generated form of in-place flexible architecture, the new by copy theory originated from work by Swick [16] for transform may be conveniently calculated using Walsh functions. -
LU Decomposition - Wikipedia, the Free Encyclopedia
LU decomposition - Wikipedia, the free encyclopedia http://en.wikipedia.org/wiki/LU_decomposition From Wikipedia, the free encyclopedia In linear algebra, LU decomposition (also called LU factorization) is a matrix decomposition which writes a matrix as the product of a lower triangular matrix and an upper triangular matrix. The product sometimes includes a permutation matrix as well. This decomposition is used in numerical analysis to solve systems of linear equations or calculate the determinant of a matrix. LU decomposition can be viewed as a matrix form of Gaussian elimination. LU decomposition was introduced by mathematician Alan Turing [1] 1 Definitions 2 Existence and uniqueness 3 Positive definite matrices 4 Explicit formulation 5 Algorithms 5.1 Doolittle algorithm 5.2 Crout and LUP algorithms 5.3 Theoretical complexity 6 Small example 7 Sparse matrix decomposition 8 Applications 8.1 Solving linear equations 8.2 Inverse matrix 8.3 Determinant 9 See also 10 References 11 External links Let A be a square matrix. An LU decomposition is a decomposition of the form where L and U are lower and upper triangular matrices (of the same size), respectively. This means that L has only zeros above the diagonal and U has only zeros below the diagonal. For a matrix, this becomes: An LDU decomposition is a decomposition of the form where D is a diagonal matrix and L and U are unit triangular matrices, meaning that all the entries on the diagonals of L and U LDU decomposition of a Walsh matrix 1 of 7 1/11/2012 5:26 PM LU decomposition - Wikipedia, the free encyclopedia http://en.wikipedia.org/wiki/LU_decomposition are one. -
Perron Spectratopes and the Real Nonnegative Inverse Eigenvalue Problem
Perron Spectratopes and the Real Nonnegative Inverse Eigenvalue Problem a b, Charles R. Johnson , Pietro Paparella ∗ aDepartment of Mathematics, College of William & Mary, Williamsburg, VA 23187-8795, USA bDivision of Engineering and Mathematics, University of Washington Bothell, Bothell, WA 98011-8246, USA Abstract Call an n-by-n invertible matrix S a Perron similarity if there is a real non- 1 scalar diagonal matrix D such that SDS− is entrywise nonnegative. We give two characterizations of Perron similarities and study the polyhedra (S) := n 1 C x R : SDxS− 0;Dx := diag (x) and (S) := x (S): x1 = 1 , whichf 2 we call the Perron≥ spectracone andgPerronP spectratopef 2, respectively. C Theg set of all normalized real spectra of diagonalizable nonnegative matrices may be covered by Perron spectratopes, so that enumerating them is of interest. The Perron spectracone and spectratope of Hadamard matrices are of par- ticular interest and tend to have large volume. For the canonical Hadamard matrix (as well as other matrices), the Perron spectratope coincides with the convex hull of its rows. In addition, we provide a constructive version of a result due to Fiedler ([9, Theorem 2.4]) for Hadamard orders, and a constructive version of [2, Theorem 5.1] for Sule˘ımanova spectra. Keywords: Perron spectracone, Perron spectratope, real nonnegative inverse eigenvalue problem, Hadamard matrix, association scheme, relative gain array 2010 MSC: 15A18, 15B48, 15A29, 05B20, 05E30 1. Introduction The real nonnegative inverse eigenvalue problem (RNIEP) is to determine arXiv:1508.07400v2 [math.RA] 19 Nov 2015 which sets of n real numbers occur as the spectrum of an n-by-n nonnegative matrix. -
The Heisenberg-Weyl Group W (Z2 )
Symmetry and Sequence Design I: m The Heisenberg-Weyl Group W (Z2 ) Robert Calderbank Stephen Howard Bill Moran Princeton University Defence Science & Technology Melbourne University Organization Australia Maximal X - Z = H−1XH Commutative Subgroup Walsh Dirac Orthonormal Basis - Sequences Sequences Supported by Defense Advanced Research Projects Agency and Air Force Office of Scientific Research D4: The Symmetry Group of the Square 0 1 1 0 Generated by matrices x = ( 1 0 ) and z = 0 −1 π xz = 0 −1 anticlockwise rotation by 1 0 2 1 0 z = 0 −1 reflection in the horizontal axis D4 is the set of eight 2 × 2 matrices ε D(a, b) given by 0 1 a 1 0 b ε D(a, b) = ε ( 1 0 ) 0 −1 where ε = ±1 and a, b = 0 or 1. 2 2 x = z = I2 1 1 1 zx = −1 ( 1 ) = −1 # xz = −zx 1 1 −1 xz = ( 1 ) −1 = 1 The Hadamard Transform H = √1 + + reflects the lattice of subgroups across the central 2 2 + − axis of symmetry D4 2 −1 H2 = I2 and H2 = H2 h±xi hxzi h±zi H2xH2 = z hxi h−xi h−I2i h−zi hzi H2zH2 = x hI2i a b a b a b ab b a H2[εx z ]H2 = ε(H2x H2)(H2z H2) = εz x = (−1) x z ab H2[εD(a, b)]H2 = (−1) εD(b, a) Kronecker Products of Matrices Given a p × p matrix X = [xij ] and a q × q matrix Y = [Yij ], the Kronecker products X ⊗ Y is defined by x11Y ... x1pY . -
Fast Random Projections Using Lean Walsh Transforms
Fast Random Projections using Lean Walsh Transforms Abstract We present a random projection matrix that is applicable to vectors x 2 Rd in O(d) operations if 0 d ¸ k2+± for arbitrary small ±0 and k = O(log(n)="2). The projection succeeds with probability 1 ¡ 1=n ¡(1+±) and it preserves lengths up to distortion " for all vectors such that kxk1 · kxk2k for arbitrary small ±. Previous results are either not applicable in linear time or require a bound on kxk1 that depends on d. 1 Introduction We are interested in producing a random projection procedure such that applying it to a vector in Rd requires O(d) operation. The idea is to ¯rst project an incoming vector x 2 Rd into an intermediate dimension d~ = d® (0 < ® < 1) and then use a known construction to project it further down to the minimal Johnson 2 Lindenstrauss (JL) dimension k = O(log(n)=" )). The mapping is composed of three matrices x 7! RADsx. ~ The ¯rst, Ds, is a random §1 diagonal matrix. The second, A, is a dense matrix of size d £ d termed the Lean Walsh Matrix. The third, R, is a k £ d~ Fast Johnson Lindenstrauss matrix. As R, we use the fast JL construction by Ailon and Liberty [2]. Their matrix, R, can be applied ~ ~ 2+±00 00 (2+±00)=® to ADsx in O(d log(k)) operations as long as d ¸ k for arbitrary small ± . If d > k this 1 condition is met . Therefore, for such d, applying R to ADsx is length preserving w.p and accomplishable in O(d~log(k)) = O(d® log(k)) = O(d) operations. -
A Multiscale Model of Nucleic Acid Imaging
Scientific Visualization, 2020, volume 12, number 3, pages 61 - 78, DOI: 10.26583/sv.12.3.06 A multiscale model of nucleic acid imaging I.V. Stepanyan1 Institute of Machine Science named after A.A.Blagonravov of the RAS 1 ORCID: 0000-0003-3176-5279, [email protected] Abstract The paper describes new results in the field of algebraic biology, where matrix methods are used [Petukhov, 2008, 2012, 2013; Petuhov, He, 2010] with the transition from matrix algebra to discrete geometry and computer visualization of the genetic code. The algorithms allow to display the composition of sequences of nitrogenous bases in parametric spaces of various dimensions. Examples of visualization of the nucleotide composition of genetic se- quences of various species of living organisms are given. The analysis was carried out in the spaces of binary orthogonal Walsh functions taking into account the physical and chemical parameters of the nitrogen bases. The results are compared with the rules of Erwin Chargaff concerning genetic sequences in the composition of DNA molecules. The developed method makes it possible to substantiate the relationship between DNA and RNA molecules with fractal and other geometric mosaics, reveals the orderliness and symmetries of polynucleotide chains of nitrogen bases and the noise immunity of their visual representations in the orthog- onal coordinate system. The proposed methods can serve to simplify the researchers' percep- tion of long chains of nitrogenous bases through their geometrical visualization in parametric spaces of various dimensions, and also serve as an additional criterion for classifying and identifying interspecific relationships. Keywords: visualization algorithms, Walsh functions, Chargaff’s rules, multidimension- al analysis, nucleotide composition, fractals, bioinformatics, DNA, chromosomes, symme- tries. -
A Novel 4-Point Discrete Fourier Transforms Circuit Based on Product of Rademacher Functions
The 5th International Conference on Electrical Engineering and Informatics 2015 August 10-11, 2015, Bali, Indonesia A Novel 4-Point Discrete Fourier Transforms Circuit based on Product of Rademacher Functions Zulfikar1, Hubbul Walidainy2 Department of Electrical Engineering Syiah Kuala University Banda Aceh 23111, Indonesia. E-mail: [email protected], [email protected] Abstract—This paper presents a new circuit design for algorithms have been developed for certain purposes and each implementing 4-point DFT algorithm based on product of of them comes with advantages and drawbacks. Rademacher functions. The circuit has been derived from the similarity of how Fourier transforms and Walsh transforms are Walsh transforms algorithm is simpler than Fourier implemented. Walsh matrices contain numbers either +1 or -1 transform, but this transformation model is rarely used in except for first row. Similarly, the 4-point DFT matrix contain application and almost forgotten. Walsh transforms has a few numbers either positive or negative except for first row. This similarity to the Fourier transforms [2]-[5]. Based on this, some similarity has been taken into the case of how to implement the researchers have adopted this algorithm for developing the DFT circuit based on how Walsh transforms is generated. Since more efficient Fourier transforms [6]-[8]. An algorithm for Walsh transforms is derived based on product of Rademacher calculating DFT using Walsh transforms is developed through functions, the proposed 4-point DFT circuit is designed according the factorization of intermediate transform T [6]. Monir T et al to product Rademacher functions. The circuit consist of negative proposed an efficient combination of Walsh and DFT circuit, multiplexers, accumulator (real and imaginary), buffers, calculation. -
Accelerated Dense Random Projections
Accelerated Dense Random Projections A Dissertation Presented to the faculty of the Graduate School of Yale University in Candidacy for the degree of Doctor of Philosophy by Edo Liberty Dissertation Director: Steven Zucker May 2009 Accelerated Dense Random Projections Edo Liberty May 2009 ABSTRACT In dimensionality reduction, a set of points in Rd is mapped into Rk, with the target dimension k smaller than the original dimension d, while distances between all pairs of points are approximately preserved. Currently popular methods for achieving this involve random projection, or choosing a linear mapping (a k £ d matrix) from a distribution that is independent of the input points. Applying the mapping (chosen according to this distribution) is shown to give the desired property with at least constant probability. The contributions in this thesis are twofold. First, we provide a framework for designing such distributions. Second, we derive e±cient random projection algorithms using this framework. Our results achieve performance exceeding other existing approaches. When the target dimension is signi¯cantly smaller than the original dimension we gain signi¯cant improvement by designing e±cient algorithms for applying certain linear algebraic transforms. To demonstrate practicality, we supplement the theoretical derivations with experimental results. Acknowledgments: Special thanks to Steven Zucker, Nir Ailon, Daniel Spielman, Ronald Coifman, Amit Singer and Mark Tygert. Their work, ideas and guidance can be seen throughout this manuscript. 1. LIST OF COMMON NOTATIONS d . .input vectors' original dimension Rd ...............................................................................real d dimensional space d x or xi . .input vector(s) in R n . number of input vectors or a constant polynomial in that number k . -
New Perspectives on Non-Negative Matrix Factorization for Grouped Topic Models
New Perspectives on Non-negative Matrix Factorization for Grouped Topic Models by Gabriel C. Phelan B.Sc., Rochester Institute of Technology, 2017 Project Submitted in Partial Fulfillment of the Requirements for the Degree of Master of Science in the Department of Statistics and Actuarial Science Faculty of Science c Gabriel C. Phelan 2020 SIMON FRASER UNIVERSITY Summer 2020 Copyright in this work rests with the author. Please ensure that any reproduction or re-use is done in accordance with the relevant national copyright legislation. Approval Name: Gabriel C. Phelan Degree: Master of Science (Statistics) Title: New Perspectives on Non-negative Matrix Factorization for Grouped Topic Models Examining Committee: Chair: Jinko Graham Professor David Campbell Senior Supervisor Professor School of Mathematics and Statistics Carleton University Lloyd T. Elliott Supervisor Assistant Professor Thomas M. Loughin Internal Examiner Professor Date Defended: August 18, 2020 ii Abstract Probabilistic topic models (PTM’s) have become a ubiquitous approach for finding a set of latent themes (“topics”) in collections of unstructured text. A simpler, linear algebraic technique for the same problem is non-negative matrix factorization: we are given a matrix with non-negative entries and asked to find a pair of low-rank matrices, also non-negative, whose product is approximately the original matrix. A drawback of NMF is the non-convex nature of the optimization problem it poses. Recent work by the theoretical computer sci- ence community addresses this issue, utilizing NMF’s inherent structure to find conditions under which the objective function admits convexity. With convexity comes tractability, and the central theme of this thesis is the exploitation of this tractability to ally NMF with resampling-based nonparametrics. -
Recent Developments in the Theory of Walsh Series
I nternat. J. Math. & Math. Sci. 625 Vol. 5 No. 4 (I982) 625-673 RECENT DEVELOPMENTS IN THE THEORY OF WALSH SERIES WILLIAM R. WADE Department of Mathematics University of Tennessee Knoxville, Tennessee 37916 U.S.A. (Received May 20, 1982) ABSTRACT. We survey research done on the theory of Walsh series during the decade 1971-1981. Particular attention is given to convergence of Walsh-Fourier series, gap Walsh series, growth of Walsh-Fourier coefficients, dyadic differentiation, and uniqueness of Walsh series. KEY WORDS AND PHRASES. Walsh-Paley system, dyadic group, maximal functns, dyadic Hp space, BMO, Vilenkin gups, weak type (p,p) dyadic differentiation. 980 MATHEMATICS SUBJECT CLASSIFICATION CODES. 42C10, 43A75. I. INTRODUCTION. This article surveys recent results on Walsh series. To avoid duplication of material appearing in Balaov and Rubintein [1970], a decision was made to concen- trate on the decade 1971-1981. References to earlier work will be made when neces- sary to relate what is herein reported to that which preceeded it. Discussion of the relationships between this material and the general theory of orthogonal series has been left to those more qualified for this task (e.g., Ul'janov [1972], Olevskii [1975] and Bokarev [1978b])o In addition to this introductory section, there remain five sections: II. Walsh-Fourier Series, III. Approximation by Walsh Series, IV. Walsh-Fourier Coefficients, V. Dyadic Differentiation, and VI. Uniqueness. These sections have been further divided into consecutively numbered subsections, each dealing with a 626 W.R. WADE particular facet of the subject and each carrying a descriptive title to help the reader quickly find those parts which interest him most. -
Human Identification Using Compressed ECG Signals
This is a postprint version of the following published document: C. Camara, P. Peris-Lopez, and J. E. Tapiador (2015). Human Identification Using Compressed ECG Signals. Journal of Medical Systems, 39: 148. Avalaible in https://doi.org/10.1007/s10916-015-0323-2 © Springer Science+Business Media New York 2015 Human ldentification Using Compressed ECG Signals Carmen Camara1 • Pedro Peris-Lopez1 • Juan E. Tapiador1 Abstract As a result of the increased demand for improved Introduction life styles and the increment of senior citizens over the age of 65, new home care services are demanded. Simul According to [3], the medica! sector is the area that has taneously, the medica! sector is increasingly becoming the suffered the major number of hacking incidents over the new target of cybercrirninals due the potential value of last two year�3 % of the data breaches in US. Medica! users' medica! information. Toe use of biometrics seems companies and hospitals have begun to introduce biometric an effective tool as a deterrent for many of such attacks. solutions to rnitigate attacks and reduce costs. Further In this paper, we propase the use of electrocardiograms more, the proper identification of patients when they walk (ECGs) for the identification of individuals. For instance, through the door is a major issue nowadays for all the for a telecare service, a user could be authenticated using hospitals around the world. Errors in medica} records, or the information extracted from her ECG signa!. Toe major even incorrect treatrnents, are very costly for the medica! ity of ECG-based biometrics systems extract information centres and harmful for the patient.