Access

You are not currently logged in.

Access your personal account or get JSTOR access through your library or other institution:

login

Log in to your personal account or through your institution.

Maximum Entropy Reconstruction Using Derivative Information, Part 1: Fisher Information and Convex Duality

J. M. Borwein, A. S. Lewis and D. Noll
Mathematics of Operations Research
Vol. 21, No. 2 (May, 1996), pp. 442-468
Published by: INFORMS
Stable URL: http://www.jstor.org/stable/3690242
Page Count: 27
  • Download ($30.00)
  • Cite this Item
Maximum Entropy Reconstruction Using Derivative Information, Part 1: Fisher Information and Convex Duality
Preview not available

Abstract

Maximum entropy spectral density estimation is a technique for reconstructing an unknown density function from some known measurements by maximizing a given measure of entropy of the estimate. Here we present a variety of new entropy measures which attempt to control derivative values of the densities. Our models apply among others to the inference problem based on the averaged Fisher information measure. The duality theory we develop resembles models used in convex optimal control problems. We present a variety of examples, including relaxed moment matching with Fisher information and best interpolation on a strip.

Page Thumbnails

  • Thumbnail: Page 
442
    442
  • Thumbnail: Page 
443
    443
  • Thumbnail: Page 
444
    444
  • Thumbnail: Page 
445
    445
  • Thumbnail: Page 
446
    446
  • Thumbnail: Page 
447
    447
  • Thumbnail: Page 
448
    448
  • Thumbnail: Page 
449
    449
  • Thumbnail: Page 
450
    450
  • Thumbnail: Page 
451
    451
  • Thumbnail: Page 
452
    452
  • Thumbnail: Page 
453
    453
  • Thumbnail: Page 
454
    454
  • Thumbnail: Page 
455
    455
  • Thumbnail: Page 
456
    456
  • Thumbnail: Page 
457
    457
  • Thumbnail: Page 
458
    458
  • Thumbnail: Page 
459
    459
  • Thumbnail: Page 
460
    460
  • Thumbnail: Page 
461
    461
  • Thumbnail: Page 
462
    462
  • Thumbnail: Page 
463
    463
  • Thumbnail: Page 
464
    464
  • Thumbnail: Page 
465
    465
  • Thumbnail: Page 
466
    466
  • Thumbnail: Page 
467
    467
  • Thumbnail: Page 
468
    468