| 1. |
- Cedervall, Mats, et al.
(författare)
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A new upper bound on the first-event error probability for maximum-likelihood decoding of fixed binary convolutional codes
- 1984
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Ingår i: IEEE Transactions on Information Theory. - 0018-9448. ; 30:5, s. 762-766
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Tidskriftsartikel (refereegranskat)abstract
- An upper bound on the first-event error probability for maximum-likelihood decoding of fixed binary convolutional codes on the binary symmetric channel is derived. The bound is evaluated for rate1/2codes, and comparisons are made with simulations and with the bounds of Viterbi, Van de Meeberg, and Post. In particular, the new bound is significantly better than Van de Meeberg's bound for rates above
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| 2. |
- Lindgren, Georg
(författare)
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On the shape and duration of FM clicks
- 1983
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Ingår i: IEEE Transactions on Information Theory. - 0018-9448. ; 29:4, s. 536-543
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Tidskriftsartikel (refereegranskat)abstract
- The stochastic behavior of FM-clicks in an unmodulated carrier plus noise is studied in terms of the conditional behavior of stationary Gaussian processes after level crossings. By a systematic use of thc Slepian model processes it is shown that the normalized shape of a positive FM-click approaches a certain rational function with simple random coefficients as the carrier-to-noise ratio tends to infinity. The outcomes of this random function illustrate the typical click shapes that have been observed experimentally. The distribution of the duration of a click is studied by means of similar model processes, and its exact asymptotic density is derived. It is seen to be very similar to a Maxwell density, although of smaller order for large durations.
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| 3. |
- Lindgren, Georg
(författare)
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Shape and duration of clicks in modulated FM transmission
- 1984
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Ingår i: IEEE Transactions on Information Theory. - 0018-9448. ; 30:5, s. 728-735
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Tidskriftsartikel (refereegranskat)abstract
- Slepian model is derived for the shape of dicks in modulated FM transmission. The modulated signal may be a deterministic periodic function or a stationary stochastic process, not necessarily Gaussian. To describe the clicks one first derives the stochastic properties of noise and signal at the clicks. (For a periodic signal this amounts to giving the relative number of clicks in any given part of the period.) Then the conditional distributions of noise and signal near clicks are derived in explicit form, using the noise and signal values at the click as (random) parameters, and finally these conditional distributions are mixed into a total model for the click shapes. For increasing carrier-to-noise power ratioA^{2}/2, the Slepian model converges after normalization to a rational function with random coefficients. The amplitude of a click is shown to be of the orderA^{2}, in contrast to the unmodulated ease, where click amplitudes are of the orderA.
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| 4. |
- Ljung, Lennart, 1946-
(författare)
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Analysis of Stochastic Gradient Algorithms for Linear Regression Problems
- 1984
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Ingår i: IEEE Transactions on Information Theory. - : IEEE Information Theory Society. - 0018-9448 .- 1557-9654. ; 30:2, s. 151-160
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Tidskriftsartikel (refereegranskat)abstract
- Parameter estimation problems that can be formulated as linear regressions are quite common in many applications. Recursive (on-line, sequential) estimation of such parameters can be performed using the recursive least squares (RLS) algorithm or a stochastic gradient version of this algorithm. In this paper the convergence properties of the gradient algorithm are analyzed under the assumption that the gain tends to zero. The technique is the same as the so-called ordinary differential equation approach, but the treatment here is self-contained and includes a proof of the boundedness of the estimates. A main result is that the convergence conditions for the gradient algorithm are the same as those for the recursive least squares algorithm.
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