Fast and Provable Algorithms for Spectrally Sparse Signal Reconstruction via Low-Rank Hankel Matrix Completion

A spectrally sparse signal of order $r$ is a mixture of $r$ damped or undamped complex sinusoids. This paper investigates the problem of reconstructing spectrally sparse signals from a random subset of $n$ regular time domain samples, which can be reformulated as a low rank Hankel matrix completion problem. We introduce an iterative hard thresholding (IHT) algorithm and a fast iterative hard thresholding (FIHT) algorithm for efficient reconstruction of spectrally sparse signals via low rank Hankel matrix completion. Theoretical recovery guarantees have been established for FIHT, showing that $O(r^2\log^2(n))$ number of samples are sufficient for exact recovery with high probability. Empirical performance comparisons establish significant computational advantages for IHT and FIHT. In particular, numerical simulations on $3$D arrays demonstrate the capability of FIHT on handling large and high-dimensional real data

Identities via Bell matrix and Fibonacci matrix

AbstractIn this paper, we study the relations between the Bell matrix and the Fibonacci matrix, which provide a unified approach to some lower triangular matrices, such as the Stirling matrices of both kinds, the Lah matrix, and the generalized Pascal matrix. To make the results more general, the discussion is also extended to the generalized Fibonacci numbers and the corresponding matrix. Moreover, based on the matrix representations, various identities are derived

Transformation and reduction formulae for double q-Clausen series of type Φ1:1;μ1:2;λ

AbstractThe Sears transformations are employed to establish several general series transformations for double q-Clausen hypergeometric series of type Φ1:1;μ1:2;λ. These transformations yield further a number of reduction and summation formulae on the double basic hypergeometric series

Some identities related to reciprocal functions

AbstractThe concept of Riordan array is used on reciprocal functions, and some identities involving binomial numbers, Stirling numbers and many other special numbers are obtained

A method for rapid similarity analysis of RNA secondary structures

BACKGROUND: Owing to the rapid expansion of RNA structure databases in recent years, efficient methods for structure comparison are in demand for function prediction and evolutionary analysis. Usually, the similarity of RNA secondary structures is evaluated based on tree models and dynamic programming algorithms. We present here a new method for the similarity analysis of RNA secondary structures. RESULTS: Three sets of real data have been used as input for the example applications. Set I includes the structures from 5S rRNAs. Set II includes the secondary structures from RNase P and RNase MRP. Set III includes the structures from 16S rRNAs. Reasonable phylogenetic trees are derived for these three sets of data by using our method. Moreover, our program runs faster as compared to some existing ones. CONCLUSION: The famous Lempel-Ziv algorithm can efficiently extract the information on repeated patterns encoded in RNA secondary structures and makes our method an alternative to analyze the similarity of RNA secondary structures. This method will also be useful to researchers who are interested in evolutionary analysis