Chromatic Derivatives and Approximations in Practice—Part II: Nonuniform Sampling, Zero-Crossings Reconstruction, and Denoising

Chromatic derivatives are special, numerically robust differential operators that preserve spectral features of a signal; the associated chromatic approximations accurately capture local features of a signal. In the first part of this paper, entitled “Chromatic Derivatives and Approximations in Practice–Part I: A General Framework,” we have derived a collection of formulas and theorems which we use in this paper to demonstrate practical applications of chromatic derivatives and approximations. We present four case studies: a highly accurate (better than 170 dB) reconstruction of a signal from its nonuniformly spaced samples; a highly accurate method for obtaining timing information, such as timing of the zeros of a signal as well as timing of the zeros of its first derivative; a method of reconstruction of a sampled speech signal of 64 000 samples using such timing information only, with a reconstruction error of only about 1% of the rms of the original signal; and finally, a denoising algorithm that significantly outperforms the well-known Cadzow's denoising algorithm. The main purpose of these case studies is to illustrate the potential of chromatic derivatives and expansions and motivate DSP engineers to find applications of these novel concepts in their own practice.

[1]  T. Engin Tuncer Block-Based Methods for the Reconstruction of Finite-Length Signals From Nonuniform Samples , 2007, IEEE Transactions on Signal Processing.

[2]  Aleksandar Ignjatovic Local Approximations Based on Orthogonal Differential Operators , 2007 .

[3]  J. Yen On Nonuniform Sampling of Bandwidth-Limited Signals , 1956 .

[4]  Gil Shabat,et al.  Splines computation by subdivision and sample rate conversion , 2013 .

[5]  Gilbert G. Walter,et al.  Chromatic series for functions of slow growth , 2011 .

[6]  A. Requicha,et al.  The zeros of entire functions: Theory and engineering applications , 1980, Proceedings of the IEEE.

[7]  Robert Hummel,et al.  Reconstructions from zero crossings in scale space , 1989, IEEE Trans. Acoust. Speech Signal Process..

[8]  Laurent Condat,et al.  Cadzow Denoising Upgraded: A New Projection Method for the Recovery of Dirac Pulses from Noisy Linear Measurements , 2015 .

[9]  T. Strohmer,et al.  Efficient numerical methods in non-uniform sampling theory , 1995 .

[10]  P.P. Vaidyanathan,et al.  New sampling expansions for bandlimited signals based on chromatic derivatives , 2001, Conference Record of Thirty-Fifth Asilomar Conference on Signals, Systems and Computers (Cat.No.01CH37256).

[11]  J. Byrnes,et al.  Local signal reconstruction via chromatic differentiation filter banks , 2001, Conference Record of Thirty-Fifth Asilomar Conference on Signals, Systems and Computers (Cat.No.01CH37256).

[12]  Ramdas Kumaresan,et al.  Encoding Bandpass Signals Using Zero/Level Crossings: A Model-Based Approach , 2010, IEEE Transactions on Audio, Speech, and Language Processing.

[13]  Hyeokho Choi,et al.  Analysis and design of minimax-optimal interpolators , 1995, 1995 International Conference on Acoustics, Speech, and Signal Processing.

[14]  Akram Aldroubi,et al.  Nonuniform Sampling and Reconstruction in Shift-Invariant Spaces , 2001, SIAM Rev..

[15]  C. Eckart,et al.  The approximation of one matrix by another of lower rank , 1936 .

[16]  Aleksandar Ignjatovic,et al.  Asymptotic behaviour of some families of orthonormal polynomials and an associated Hilbert space , 2014, J. Approx. Theory.

[17]  Luis F. Chaparro,et al.  Reconstruction of nonuniformly sampled time-limited signals using prolate spheroidal wave functions , 2009, Signal Process..

[18]  C. Narduzzi,et al.  Digital time of flight measurement for ultrasonic sensors , 1991, [1991] Conference Record. IEEE Instrumentation and Measurement Technology Conference.

[19]  Yonina C. Eldar,et al.  Filterbank reconstruction of bandlimited signals from nonuniform and generalized samples , 2000, IEEE Trans. Signal Process..

[20]  Håkan Johansson,et al.  Reconstruction of nonuniformly sampled bandlimited signals by means of digital fractional delay filters , 2002, IEEE Trans. Signal Process..

[21]  Gilbert G. Walter,et al.  Discrete chromatic series , 2011 .

[22]  Subhash Kak Zero-crossing information for signal reconstruction , 1969 .

[23]  Gilbert G. Walter,et al.  Prolate Spheroidal Wave Functions and Wavelets , 2006 .

[24]  Ahmed I. Zayed,et al.  Generalizations of Chromatic Derivatives and Series Expansions , 2010, IEEE Transactions on Signal Processing.

[25]  Aleksandar Ignjatovic Chromatic Derivatives, Chromatic Expansions and Associated Spaces , 2009 .

[26]  Yannis P. Tsividis,et al.  Derivative Level-Crossing Sampling , 2015, IEEE Transactions on Circuits and Systems II: Express Briefs.

[27]  Ahmed I. Zayed Chromatic Expansions and the Bargmann Transform , 2013 .

[28]  Ryan J. Pirkl,et al.  Covariance Matrix Estimation for Broadband Underwater Noise , 2017, IEEE Journal of Oceanic Engineering.

[29]  Borislav Savković Decorrelating Properties of Chromatic Derivative Signal Representations , 2010, IEEE Signal Processing Letters.

[30]  Xiaoping Shen,et al.  A sampling expansion for nonbandlimited signals in chromatic derivatives , 2005, IEEE Transactions on Signal Processing.

[31]  P.P. Vaidyanathan,et al.  Chromatic derivative filter banks , 2002, IEEE Signal Processing Letters.

[32]  B. Logan Information in the zero crossings of bandpass signals , 1977, The Bell System Technical Journal.

[33]  Thippur V. Sreenivas,et al.  Sparse signal reconstruction based on signal dependent non-uniform samples , 2012, 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[34]  P.P. Vaidyanathan,et al.  Finite-channel chromatic derivative filter banks , 2003, IEEE Signal Processing Letters.

[35]  James J. Clark,et al.  A transformation method for the reconstruction of functions from nonuniformly spaced samples , 1985, IEEE Trans. Acoust. Speech Signal Process..

[36]  P. Misans,et al.  CW doppler radar based land vehicle speed measurement algorithm using zero crossing and least squares method , 2012, 2012 13th Biennial Baltic Electronics Conference.

[37]  Andrew P. Witkin,et al.  Scale-Space Filtering , 1983, IJCAI.

[38]  Aleksandar Ignjatovic Chromatic Derivatives and Local Approximations , 2009, IEEE Transactions on Signal Processing.

[39]  Petre Stoica,et al.  Introduction to spectral analysis , 1997 .

[40]  T. Poggio,et al.  Fingerprints theorems for zero crossings , 1985 .

[41]  Wu Fang,et al.  Binaural Sound Localization Based on Detection of Multi-band Zero-crossing Points , 2009 .

[42]  James A. Cadzow,et al.  Signal enhancement-a composite property mapping algorithm , 1988, IEEE Trans. Acoust. Speech Signal Process..

[43]  Arjuna Madanayake,et al.  DOA-estimation and source-localization in CR-networks using steerable 2-D IIR beam filters , 2013, 2013 IEEE International Symposium on Circuits and Systems (ISCAS2013).

[44]  Zhaohui Li,et al.  Robust Precise Time Difference Estimation Based on Digital Zero-Crossing Detection Algorithm , 2016, IEEE Transactions on Instrumentation and Measurement.

[45]  Cornel Ioana,et al.  Advanced signal processing techniques for detection and localization of electrical arcs , 2014, 2014 10th International Conference on Communications (COMM).

[46]  Y Wang,et al.  On representing signals using only timing information. , 2001, The Journal of the Acoustical Society of America.

[47]  Yoel Shkolnisky,et al.  Approximation of bandlimited functions , 2006 .

[48]  Thomas Strohmer,et al.  Numerical analysis of the non-uniform sampling problem , 2000 .

[49]  Farrokh Marvasti,et al.  Recovery of signals from nonuniform samples using iterative methods , 1991, IEEE Trans. Signal Process..

[50]  V. Rokhlin,et al.  Prolate spheroidal wavefunctions, quadrature and interpolation , 2001 .