Short codes with a given covering radius

The covering radius r of a code is the maximum distance from any vector in the space containing the code to the nearest codeword. The authors introduce a new function l(m,r), called the length function, which equals the smallest length of a binary code of codimension m and covering radius r. They investigate basic properties of the length function. Projective geometries over larger fields are used to construct families of codes which improve significantly the upper bound for l(m,2) obtained by amalgamation of Hamming codes. General methods are developed for ruling out the existence of codes of covering radius 2 with a given codimension and length resulting in lower bounds for l(m,2). A table is presented which gives the best results now known for l(m,r) with m⩽12 and r⩽12     

A binary analog to the entropy-power inequality

Let {X_n}, {Y_n} be independent stationary binary random sequences with entropy H( X), H(Y), respectively. Let h(ζ)=-ζlogζ-(1-ζ)log(1-ζ), 0⩽ζ⩽1/2, be the binary entropy function and let σ(X)=h^-1 (H(X)), σ(Y)=h^-1 (H(Y)). Let z_n=X_n⊕Y_n , where ⊕ denotes modulo-2 addition. The following analog of the entropy-power inequality provides a lower bound on H(Z ), the entropy of {Z_n}: σ(Z)⩾σ(X)*σ(Y), where σ(Z)=h^-1 (H(Z)), and α*β=α(1-β)+β(1-α). When {Y _n} are independent identically distributed, this reduces to Mrs. Gerber's Lemma from A.D. Wyner and J. Ziv (1973)     

Relationships between m-sequences over GF(q) andGF(qm)

It is shown that m-sequences over GF(q^m ) of length q^nm-1 corresponding to primitive polynomials in GF[q^m,x] of degree n can be generated from known m-sequences over GF(q) of length q^nm-1 obtained from primitive polynomials in GF[q,x] of degree mn. A procedure for generating the m-sequences over GF(q²) from m-sequences over GF(q) was given which enables the generation of m-sequences over GF( p²ⁿ). In addition it was shown that all of the primitive polynomials in GF[q,^m,x] can be obtained from a complete set of the primitive polynomials in GF[q ,x]     

Capacity of the Gaussian arbitrarily varying channel

The Gaussian arbitrarily varying channel with input constraint Γ and state constraint Λ admits input sequences x=(x₁,---,X_n) of real numbers with Σx_i²⩽nΓ and state sequences s=(S₁,---,s_n ) of real numbers with Σs_i²⩽nΛ; the output sequence x+s+V, where V=(V₁,---,V_n) is a sequence of independent and identically distributed Gaussian random variables with mean 0 and variance σ². It is proved that the capacity of this arbitrarily varying channel for deterministic codes and the average probability of error criterion equals 1/2 log (1+Γ/(Λ+σ²)) if Λ<Γ and is 0 otherwise     

Constructions of error-correcting DC-free block codes

Two DC-free codes are presented with distance 2d, b ⩾1 length 2n+2r(d-1) for d⩽3 and length 2n+2r(d-1)(2d -1) for d>3, where r is the least integer ⩾log₂ (2n+1). For the first code l=4, c=2, and the asymptotic rate of this code is 0.7925. For the second code l=6, c=3, and the asymptotic rate of this code is 0.8858. Asymptotically, these rates achieve the channel capacity. For small values of n these codes do not achieve the best rate. As an example of codes of short length with good rate, the author presents a (30, 10, 6, 4) DC-free block code with 2²¹ codewords. A construction is presented for which from a given code C ₁ of length n, even weight, and distance 4, the author obtains a (4n, l, c, 4) DC-free block code C₂, where l is 4, 5 or 6, and c is not greater than n+1 (but usually significantly smaller). The codes obtained by this method have good rates for small lengths. The encoding and decoding procedures for all the codes are discussed     

A storage-efficient method for solving banded Toeplitz systems

A method is presented for solving the banded Toeplitz system Tx=y by decomposing T into its asymptotic upper and lower triangular factors (which are banded and Toeplitz) and a rank-p correction matrix, where p is the bandwidth of T. This way of representing T requires only O(p²) words of storage and allows computation of x in O(2Np) operations. A similar method is presented for the case in which T is bi-infinite and y is zero outside a finite region     

Confidence bounds for Pr{X>Y} in 1-way ANOVArandom model

Approximate confidence bounds for reliability, R=Pr{X >Y|X,Y}, are obtained, where X and Y are independent normal (Gaussian) random variables, and X and Y are vectors of measurements for X and Y, respectively. Balanced 1-way ANOVA (analysis of variants) random effect models are assumed for the populations of X and Y. Confidence bounds are derived for R under three cases for standard deviations, σ_x and σ_y. An example shows how the results are used     

Binary [18,11]2 codes do not exist-Nor do [64,53]2 codes

A binary, linear block code C with block length n and dimension n is commonly denoted by [n, k] or, if its minimum distance is d, by [n, k,d]. The code's covering radius r(C) can be defined as the smallest number r such that any binary column vector of length (n-k) can be written as a sum of r or fewer columns of a parity-check matrix of C. An [n,k] code with covering radius r is denoted by [n,k]r. R.A. Brualdi et al., (1989) showed that l(m,r) is defined to be the smallest n such that an [n,n-m]r code exists. l(m,2) is known for m⩽6, while it is shown by Brualdi et al. that 17⩽l(7,2)⩽19. This lower bound is improved by A.R. Calderbank et al. (1988), where it is shown that [17,10]2 codes do not exist. The nonexistence of [18,11]2 codes is proved, so that l(7,2)=19. l[7.2)=19 is established by showing that [18,11]2 codes do not exist. It is also shown that [64,53]2 codes do not exist, implying that l(11,2)⩾65     

Multiterminal source encoding with one distortion criterion

The authors unify earlier investigations concerning the encoding of two correlated sources {X_k}, {Y_k } by means of separate encoders. Decoding is done by a single decoder which receives the outputs from both encoders. The reconstruction of {X_k} is required to be perfect in the usual Shannon sense. The authors determine the admissible rate region R (D), where D is the distortion of the reconstruction of {Y_k}. The binary Hamming case is investigated explicitly     

Optimal probability-of-error thresholds and performance for twoversions of the sign detector

Expressions are obtained for specifying the optimal error probability (minimum P_e) thresholds λ₀₁ and λ₀₂ for the traditional and modified sign detectors, respectively. These thresholds are shown to depend on the parameters p, P₁, and M where: M is the number of observations z_i used in the test statistic; P₁=P(H₁ ) is the prior probability for hypothesis H₁ that signal s₁ is present and 1-P₁ =P(H₀) corresponds to the hypothesis H₀ that signal s₀ is present; and p=Pr{z_i⩾0|H₁} with s₀=0 for the traditional sign detector and p=Pr{z_i⩾λ|H₁ }=Pr{z_i<λ|H₀} with λ =(s₀+s₁)/2 for the modified sign detector. The expressions for λ₀₁ and λ₀₂, are given explicitly, and shown to be independent of P₁ for sufficiently large M. Optimal P_e versus M performance curves, corresponding to both versions of the sign detector, are obtained for a representative range of values for p and P₁     

Numerical evaluation of parabolic cylinder functions

The numerical evaluation of the parabolic cylinder functions D _p(z) in two cases is described. Case I is for the argument z=xe^-iπ/4, with x real, and the order p=-1/2+iy, with y real. Case II is for z arbitrary, but p an integer. These cases are of special importance in the analysis of wave scattering from a parabolic cylinder. Expressions for D_p(z) are presented which are numerically accurate and efficient     

The entropy theorem via coding bounds

The entropy theorem (also known as the Shannon-McMillan-Breiman theory or the asymptotic equipartition theorem) asserts that, for a stationary ergodic finite alphabet process, the sequence-(1/n)log p(x₁ⁿ) converges almost surely to the entropy-rate H of the process. The entropy theorem has been used to establish asymptotic bounds on the performance of noiseless codes. Here, the coding theorems are established without using the entropy theorem, and the coding theorems are then used to prove the entropy theorem. The principle feature is the direct use of coding ideas to obtain the entropy theorem     

Bias in a stress-strength problem

The bias of the maximum likelihood estimator for R≠Pr{ X<Y} where X and Y are independent normal random variables with unknown parameters is discussed. The bias is an odd function with respect to δ=gauf^-1 (R), where gauf(·) is the Cdf of the standard normal distribution, so the study is restricted to R ⩾0.5, or equivalently, δ⩾0. There exists δ₀>0 such that the bias is positive in the interval 0<δ<δ₀. R has a positive bias at least in the interval 0.84<R<0.94     

Convergence of filters with applications to the Kalman-Bucy case

For each N, and each fixed time T, a signal X^N and a `noisy' observation Y^N are defined by a pair of stochastic difference equations. Under certain conditions (X^N, Y^N) converges in distribution to (X, Y, where dX(t)= f(t, X(t))dt+dV( t), dY(t)=g(t, X( t))dt+dW(t). Conditions are found under which convergence in distribution of the conditional expectations E{F(X^N)|Y^N} to E{F(X)|Y} follows, for every bounded continuous function F. The case in which the conditional expectations still converge but the limit is not E{ F(X)|Y} is also studied. In the situation where f and g are linear functions of X, an examination of this limit leads to a Kalman-Bucy-type estimate of X ^N which is asymptotically optimal and is an improvement on the usual Kalman-Bucy estimate     

A (16, 9, 6, 5, 4) error-correcting DC free block code

A (2n, k, l, c, d) DC free binary block code is a code of length 2n, constant weight n, 2^k codewords, maximum runlength of a symbol l , maximum accumulated charge c, and minimum distance d . The purpose of this code is to achieve DC freeness and error correction at the same time. The goal is to keep the rate k/2 n and d large and l and c small. Of course, these are conflicting goals. H.C. Ferreira (IEEE Trans. Magn., vol.MAG-20, no.5, p.881-3, 1984) presented a (16, 8, 8, 5, 4) DC free code. Here, a (16, 9, 6, 5, 4) DC free code is presented. Easy encoding and decoding algorithms are also given     

On the existence of optimum cyclic burst correcting codes over GF(q)

A cyclic b-burst correcting code over GF(q) of redundancy r and length n=(q^r-b+1-1)/(q-1) is said to be optimum. It is proved that a necessary condition for the existence of such a code is the existence of a square-free polynomial in GF(q)[x] of degree b-1 which is not divisible by x such that its period and the degrees of its irreducible factors are relatively prime to q-1. Moreover, if such a polynomial exists, then there are an infinite number of optimum cyclic b-burst correcting codes over GF(q)     

Robustness of mean E{X} and R charts

The effect of nonnormality on E{X} and R charts is reported. The effect of departure from normality can be examined by comparing the probabilities that E{X} and R lie outside their three-standard-deviation and two-standard-deviation control limits. Tukey's λ-family of symmetric distributions is used because it contains a wide spectrum of distributions with a variety of tail areas. The constants required to construct E{X} and R charts for the λ-family are computed. Control charts based on the assumption of normality give inaccurate results when the tails of the underlying distribution are thin or thick. The validity of the normality assumption is examined by using a numerical example     

Weight enumerators of self-dual codes

Some construction techniques for self-dual codes are investigated, and the authors construct a singly-even self-dual [48,24,10]-code with a weight enumerator that was not known to be attainable. It is shown that there exists a singly-even self-dual code C' of length n =48 and minimum weight d=10 whose weight enumerator is prescribed in the work of J.H. Conway et al. (see ibid., vol.36, no.5, p.1319-33, 1990). Two self-dual codes of length n are called neighbors, provided their intersection is a code of dimension (n/2)-1. The code C' is a neighbor of the extended quadratic residue code of length 48     

An updating algorithm for subspace tracking

In certain signal processing applications it is required to compute the null space of a matrix whose rows are samples of a signal with p components. The usual tool for doing this is the singular value decomposition. However, the singular value decomposition has the drawback that it requires O(p³) operations to recompute when a new sample arrives. It is shown that a different decomposition, called the URV decomposition, is equally effective in exhibiting the null space and can be updated in O( p²) time. The updating technique can be run on a linear array of p processors in O(p) time     

Optimal codes for correcting single errors and detecting adjacenterrors

Optimal codes that correct single errors and detect double errors within nibbles of power of two length are presented. For each n, a code of length n with the largest possible dimension which corrects single errors and detects double adjacent errors is presented. The problem of constructing optimal codes which correct single errors and detect double adjacent errors within nibbles of length l is discussed