A Year Like No Other

Animated short film that I scored from a Director in LA.https://remix.berklee.edu/graduate-studies-scoring/1164/thumbnail.jp

An Image Model based on Occluding Object Images and Maximum Entropy

This Paper Introduces a Statistical Image Model based on Occlusion and Maximum Entropy. the Statistical Model Combines a Fundamental Property of Image Formation, Occlusion, with Both Object-Image Shape and Nonuniform Object-Image Intensity. the Model is a Composition of Individual Object-Images that Have Random Positions, Shapes, and Intensities, and that Occlude Both Background and One Another. We Derive the Autocorrelation and Second-Order Probability Density Functions of This Model and Give Several Examples. © 1998 IEEE

Structural Pattern Matching - Succinctly

Let T be a text of length n containing characters from an alphabet Sigma, which is the union of two disjoint sets: Sigma_s containing static characters (s-characters) and Sigma_p containing parameterized characters (p-characters). Each character in Sigma_p has an associated complementary character from Sigma_p. A pattern P (also over Sigma) matches an equal-length substring $S$ of T iff the s-characters match exactly, there exists a one-to-one function that renames the p-characters in S to the p-characters in P, and if a p-character x is renamed to another p-character y then the complement of x is renamed to the complement of y. The task is to find the starting positions (occurrences) of all such substrings S. Previous indexing solution [Shibuya, SWAT 2000], known as Structural Suffix Tree, requires Theta(nlog n) bits of space, and can find all occ occurrences in time O(|P|log sigma+ occ), where sigma = |Sigma|. In this paper, we present the first succinct index for this problem, which occupies n log sigma + O(n) bits and offers O(|P|logsigma+ occcdot log n logsigma) query time

pBWT: Achieving succinct data structures for parameterized pattern matching and related problems

The fields of succinct data structures and compressed text indexing have seen quite a bit of progress over the last two decades. An important achievement, primarily using techniques based on the Burrows-Wheeler Transform (BWT), was obtaining the full functionality of the suffix tree in the optimal number of bits. A crucial property that allows the use of BWT for designing compressed indexes is order-preserving suffix links. Specifically, the relative order between two suffixes in the subtree of an internal node is same as that of the suffixes obtained by truncating the furst character of the two suffixes. Unfortunately, in many variants of the text-indexing problem, for e.g., parameterized pattern matching, 2D pattern matching, and order-isomorphic pattern matching, this property does not hold. Consequently, the compressed indexes based on BWT do not directly apply. Furthermore, a compressed index for any of these variants has been elusive throughout the advancement of the field of succinct data structures. We achieve a positive breakthrough on one such problem, namely the Parameterized Pattern Matching problem. Let T be a text that contains n characters from an alphabet , which is the union of two disjoint sets: containing static characters (s-characters) and containing parameterized characters (p-characters). A pattern P (also over ) matches an equal-length substring S of T i the s-characters match exactly, and there exists a one-to-one function that renames the p-characters in S to that in P. The task is to find the starting positions (occurrences) of all such substrings S. Previous index [Baker, STOC 1993], known as Parameterized Suffix Tree, requires (n log n) bits of space, and can find all occ occurrences in time O(jPj log +occ), where = jj. We introduce an n log +O(n)-bit index with O(jPj log +occlog n log ) query time. At the core, lies a new BWT-like transform, which we call the Parame- terized Burrows-Wheeler Transform (pBWT). The techniques are extended to obtain a succinct index for the Parameterized Dictionary Matching problem of Idury and Schaer [CPM, 1994]