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Interval Estimates for Signal Processing: Special Purpose Hardware

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Reliable Computing

Abstract

Error estimation for the results of signal processing is traditionally based on the assumption that we know the probability distribution of the input signals. In many real-life situations, however, we only know the upper bounds for the signal's error, i.e., we only know the intervals of possible values of the input signal. In such situations, we are interested in knowing the interval of possible values of the output. The corresponding computations are often very computationally intensive; in this paper, we describe a special purpose hardware which can drastically speed up the computation of interval estimates for signal processing.

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References

  1. Burrus, C. S.: Computer-Based Exercises for Signal Processing Using MATLAB, Prentice-Hall, Englewood Cliffs, NJ, 1994.

    Google Scholar 

  2. Cathoor, F., Laneer, D., and De Man, H.: Efficient Microcoded Processor Design for Fixed Rate DFT and FFT, Journal of VLSI Signal Processing 1 (1990), pp. 287–306.

    Google Scholar 

  3. Gibson, G. A.: Six-Month Report—Investigations of Modularly Configurable Attached Processor with Intelligent Memories, Technical Report to ONR, Attachments A and B, 1995.

  4. Gibson, G. A., Singh, V. P., Singh, S. J., Liu, Y. C., Chang, Y. C., and Cabrera, S. D.: MCM Implementation of Modularly Configurable Attached Processors, in: IEEE International Computer Symposium, Taiwan, Dec. 1994, pp. 465–472.

  5. Oppenheim, A. V. and Schafer, R. W.: Discrete-Time Signal Processing, Prentice Hall, Englewood Cliffs, NJ, 1989.

    Google Scholar 

  6. Pérez-González, F., Docampo, D., and Abdallah, C.: Bounding the Frequency Response for Digital Transfer Functions: Results and Applications, in: Proc. of IEEE Digital Signal Processing Workshop, 1994, pp. 15–18.

  7. Signal Processing Handbook, Dekker, NY, 1988.

  8. Singh, S. J., Gremel, B. W., Singh, V. P., and Gibson, G. A.: Design Considerations for Implementing a Modularly Configurable Attached Processor in a Multichip Module, in: MCMC'95, Santa Cruz, CA, January 1995, pp. 62–68.

    Google Scholar 

  9. Singh, S. J., Gremel, B. W., Singh, V. P., and Gibson, G. A.: Design Issues in a CMOS Implementation of Modularly Configurable Attached Processor, Int'l J. of Electronics 78(5) (1995), pp. 945–958.

    Google Scholar 

  10. Stearns, S. D.: Signal Processing Algorithms in MATLAB, Prentice Hall, Upper Saddle River, NJ, 1996.

    Google Scholar 

  11. Van Loan, C.: Computational Frameworks for the Fast Fourier Transform, SIAM, Phil., 1992.

    Google Scholar 

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Kosheleva, O., Cabrera, S.D., Gibson, G.A. et al. Interval Estimates for Signal Processing: Special Purpose Hardware. Reliable Computing 5, 175–196 (1999). https://doi.org/10.1023/A:1009909706977

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  • DOI: https://doi.org/10.1023/A:1009909706977

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