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{"references": ["R. J. Mitchell and R. C Gonzalez, Multilevel crossing rates for automated\nsignal classification, Proc. of ICASSP-78, Volume 3, Apr 1978\nPage(s):218 222.", "H. Inose, T. Aoki and K. Wantanable, Asynchronous delta modulation\nsystems, Electron. Commun., Japan, pp.34-42, Mar. 1966.", "N. Sayiner, H. V. Sorensen and T. R. Viswanathan, A level crossing\nsampling scheme for A/D conversion, IEEE Transactions on Circuits and\nSystems II 43, April-1996, pp. 335-339.", "E. Allier, G. Sicard, L. Fesquet and M. Renaudin, Asynchronous level\ncrossing analog to digital converters, Measurement Journal, April,\n2005,Vol. 37, pp.296-309.", "Karen Guan and Andrew C. Singer, A Level Crossing Sampling Scheme\nfor Non-Bandlimited Signals, Proc. of ICASSP 2006, May 2006, Volume:\n3,pp: III-381-383.", "Marek Miskowicz, Efficiency of Level-Crossing Sampling for Bandlimited\nGaussian Random Processes, Proc. of IEEE International Workshop on\nFactory Communication Systems-2006, June 2006, pp: 137- 142", "William H. Press, Saul A. Teukolsky, T. V William and P. F Brian,\nNumerical Recipes in C++, Cambridge university press, Second Edition,\n2002.", "M. Lim and C. Saloma, Direct signal recovery from threshold crossings\nPhys. Rev. E 58, pp:6759 - 6765 (1998).", "G. Tapang and C. Saloma, Dynamic range enhancement of an optimized\n1-bit AD converter, IEEE Trans. Circuits Syst II, Vol. 49, pp. 42-47\n(2002).\n[10] I. F. Blake and W. C. Lindsey, Level-crossing problems for random\nprocesses, IEEE Transactions on Information Theory, no:3, pp. 295-315,\n1973.\n[11] F. Akopyan, R. Manohar and A. B. Apsel, A level-crossing flash\nasynchronous analog-to-digital converter, Proc. of IEEE International\nSymposium on Asynchronous Circuits and Systems 2006,pp.12-22.\n[12] Layer 7 LonMark Interoperability Guidelines, Ver. 3.2; LonMark Interoperability\nAssociation,2002.\n[13] S. C. Gupta, Increasing the sampling efficiency for a control system.\nIEEE Transactions on Automatic Control 1963, 8 (3), 263-264.\n[14] M. Miskowicz, Send-on-delta concept: an event-based data reporting\nstrategy, Sensors, Special Issue: Wireless Sensor Networks and Platforms\nvol. 6, no 1, pp. 49-63, 2006.\n[15] K. J. Astrom and B. Bernhardsson, Comparison of periodic and event\nbased sampling for first-order stochastic systems, Proc. of IFAC World\nCongress 1999, pp. 301-306.\n[16] P. Otanez, J. Moyne and D. Tilbury, Using deadbands to reduce\ncommunication in networked control systems, Proc. of American Control\nConference 2002, pp. 3015-3020.\n[17] M. Miskowicz, Asymptotic Effectiveness of the Event-Based Sampling\naccording to the Integral Criterion, Sensors, Special Issue: Wireless\nSensor Networks and Platforms vol. 6, no 1, pp. 49-63, 2006.\n[18] B. Bernhardsson,Event triggered sampling, Research problem formulations\nin the DICOSMOS project 1998, Lund Institute of Technology.\n[19] K. J. Astrom and B. Bernhardsson, Comparison of Riemann and\nLebesgue Sampling for First Order Stochastic Systems, Proc. of the 41st\nIEEE Conference on Decision and Control, Vol 2, pp. 2011- 2016, 2002.\n[20] V. Daria and C. Saloma, High-Accuracy Fourier Transform Interferometry,\nWithout Oversampling, with a 1-Bit Analog-to-Digital Converter,\nAppl. Opt. 39 108-113 (2000)\n[21] M. A. Nazario and C. Saloma, Signal Recovery in Sinusoid-Crossing\nSampling by use of the Minimum-Negativity Constraint, Appl. Opt. 37,\n2953-2963 (1998)\n[22] J. S. Garofolo and L. F. Lamel, DARPA TIMIT Acoustic-phonetic\nContinuous Speech Corpus, U.S.Department of Commerce, 1993\n[23] G. Lu, Communication and Computing for Distributed Multimedia\nSystems, Artech House, ISBN: 0-89006-884-4, 1996."]}
Although the level crossing concept has been the subject of intensive investigation over the last few years, certain problems of great interest remain unsolved. One of these concern is distribution of threshold levels. This paper presents a new threshold level allocation schemes for level crossing based on nonuniform sampling. Intuitively, it is more reasonable if the information rich regions of the signal are sampled finer and those with sparse information are sampled coarser. To achieve this objective, we propose non-linear quantization functions which dynamically assign the number of quantization levels depending on the importance of the given amplitude range. Two new approaches to determine the importance of the given amplitude segment are presented. The proposed methods are based on exponential and logarithmic functions. Various aspects of proposed techniques are discussed and experimentally validated. Its efficacy is investigated by comparison with uniform sampling.
sampling, asynchronousdelta modulation, signal reconstruction, non-linear quantization., speech signals
sampling, asynchronousdelta modulation, signal reconstruction, non-linear quantization., speech signals
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