Speech dereverberation is one of the most difficult tasks in acoustic signal processing. Of the various problems involved in this task, this paper highlights "over-whitening," which flattens the characteristics of recovered speech. This distortion sometimes happens when inverse filters are directly calculated from microphone signals. This paper reviews two studies related to this problem. The first study shows the possibility of compensating for such over-whitening to achieve precise speech-dereverberation. The second study presents a new approach for approximating the original speech by removing the effect of late reflections from observed reverberant speech.

This paper presents an efficient algorithm for computing the characteristic polynomial of a matrix, which utilizes Cayley-Hamilton's theorem. The algorithm requires no condition on input matrix and can be performed only with basic matrix operations except only one computation of inverse of constant matrix. Though the algorithm can be applied to a constant matrix, it is the most effective when applied to a matrix with polynomial entries. Computational tests are given to compare the algorithm with conventional ones.

This paper presents an efficient algorithm to compute the characteristic polynomial of a polynomial matrix. We impose the following condition on given polynomial matrix M. Let M0 be the constant part of M, i. e. M0 M ( mod (y,,z)), where y,,z are indeterminates in M. Then, all eigenvalues of M0 must be distinct. In this case, the minimal polynomial of M and the characteristic polynomial of M agree, i. e. the characteristic polynomial f(x,y,,z) | x E M | is the minimal degree (w. r. t. x) polynomial satisfying f(M,y,,z) 0. We use this fact to compute f(x,y,,z). More concretely, we determine the coefficients of f(x,y,,z) little by little with basic matrix operations, which makes the algorithm quite efficient. Numerical experiments are given to compare the algorithm with conventional ones.

One-dimensional Cellular Automata (CA's) are considered as potential pseudorandom pattern generators to generate highly random parallel patterns with simple hardware configurations. A class of linear, binary, and of nearest neighbor (radius = 1) CA's is referred to here as elementary ones. This paper investigates operations of such CA's with fixed boundary conditions when non-null boundary values are applied to them. By modifying transition matrices of elementary CA's to include the influence of boundary values, structures of state transition diagrams are determined.

Recently two interesting conjectures on the linear complexity of binary complementary sequences of length 2nN0 were given by Karkkainen and Leppanen when those sequences are considered as periodic sequences with period 2nN0, where those sequences are constructed by successive concatenations or successive interleavings from a pair of kernel complementary sequences of length N0. Their conjectures were derived from numerical examples and suggest that those sequences have very large linear complexities. In this paper we give the exact formula of characteristic polynomials for those complementary sequences and show that their conjectures are true.