Convolutional Model

  • Jerry M. Mendel
Part of the Signal Processing and Digital Filtering book series (SIGNAL PROCESS)


The basic convolutional model is (see Figure 2-1)
$${\text{measured}}\,{\text{output = output + noise = input*IR + noise}}$$
In this chapter we describe the three components of this model, i.e., input, IR, and noise so that we can compute a formula for the likelihood function. Before doing this, we pause briefly to relate the reflection seismology experiment to the convolutional model.


Colored Noise Reflectivity Function Layered Earth Gaussian Sequence Seismic Wavelet 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag New York Inc. 1990

Authors and Affiliations

  • Jerry M. Mendel
    • 1
  1. 1.Department of Electrical Engineering-SystemsUniversity of Southern CaliforniaLos AngelesUSA

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