This work presents two configurable LZSS-based compression algorithms, LZAA and LZAB, designed to optimize throughput, latency, and compression ratio. LZAA refines its configuration through a two-pass statistical analysis, while LZAB dynamically adapts configurations block-wise during compression. Experimental results demonstrate that both methods effectively achieve their performance goals, supported by a dedicated evaluation framework.

In this paper we detail a new approach for lossless integer compression that can be used to extend and improve several existing dynamic lossless data compression methods. The new methodology, referred to as Delta-Huffman, uses the Elias Delta code as a uniquely decodable representation of the infinite alphabet of unbounded integers and utilizes this representation to enable the application of dynamic Huffman coding on the Delta encoded set of integers. The method can be extended to combinations of other integer encoding techniques with additional dynamic symbol coding algorithms.

Constructive multistart search algorithms are commonly used to address combinatorial optimization problems; however, constructive multistart search algorithm performance is fundamentally affected by two factors: (i) The choice of construction algorithm utilized and (ii) the rate of state space search redundancy. Construction algorithms are typically specific to a particular combinatorial optimization problem; therefore, we first investigate construction algorithms for iterative hill climbing applied to the traveling salesman problem and experimentally determine the best performing algorithms. We then investigate the more general problem of utilizing record-keeping mechanisms to mitigate state space search redundancy. Our research shows that a good choice of construction algorithm paired with effective record keeping significantly improves the quality of traveling salesmen problem solutions in a constant number of state explorations. Particularly, we show that Bloom filters considerably improve time performance and solution quality for iterative hill climbing approaches to the traveling salesman problem.

Complex fuzzy sets utilize a complex degree of membership, represented in polar coordinates, which is a combination of a degree of membership in a fuzzy set along with a crisp phase value that denotes position within the set. The compound value carries more information than a traditional fuzzy set and enables efficient reasoning. In this paper, we present a new and generalized interpretation of a complex grade of membership, where a complex membership grade defines a complex fuzzy class. The new definition provides rich semantics that is not readily available through traditional fuzzy sets or complex fuzzy sets and is not limited to a compound of crisp cyclical data with fuzzy data. Furthermore, the two components of the complex fuzzy class carry fuzzy information. A complex class is represented either in Cartesian or in polar coordinates where both axes induce fuzzy interpretation. Another novelty of the scheme is that it enables representing an infinite set of fuzzy sets. The paper provides the new definition of complex fuzzy classes along with axiomatic definition of basic operations on complex fuzzy classes. In addition, coordinate transformation as well as an extension from two-dimensional fuzzy classes to n-dimensional fuzzy classes are presented. © 2011 Wiley Periodicals, Inc.

This paper presents integer sequences that have the property of being additively and/or multiplicatively complete, Zekendorf, and unique Zekendorf. In addition, a generalized Elias coding scheme is developed. Features of Zekendorf sequence based and generalized Elias coding compression methods including compression rate, universality, asymptotic optimality, and coding complexity are analyzed.

Summary form only given. This paper presents a new and efficient method of encoding uniform image regions and lines. Regions and lines are obtained as the result of image segmentation, split and merge image compression, or as the output of line and polygon drawing algorithms. Lines and contours of uniform regions are encoded using chain-code. The chain-code is obtained in a way that is efficient with respect to bit-rate and produces lossless contour and line encoding. A lossy method for contour encoding is also presented. A set of experiments to compare the performance of traditional chain-code contour encoding with the improved contour encoding is presented. The results show a reduction of about 50% in the bit-rate with no reconstruction error.