This thesis experiment is an exploration of Ross Data Coding (RDC) with several modifications intended to significantly improve compression efficiency. Experimental analysis show the RDC algorithm produces compression efficiency at a comparable level to other well known encoders with exceptionally low CPU and memory requirements. This thesis purpose is to explore how to increase its compression efficiency and further sacrifice CPU resources if needed. First, we study the algorithm for possibly modifications to enhance compression. Second, we combine the RDC algorithm with a statistical based algorithm to increase compression further. This resultant hybrid coder (RAH_S8) can optimize for maximum speed or compression depending on requirements. Through use of a parameter the user can select between maximum speed and compression. For maximum speed the hybrid algorithm uses modified RDC coding alone. For maximum compression the hybrid combines RDC coding with Adaptive Huffman coding. This thesis reviews background information of data compression as it pertains to this thesis. A preliminary analysis yields performance results of several traditional compression algorithms along with RDC coding. The analysis focuses on three different variables: compression efficiency, performance, and memory usage. This thesis then gives an overview of the original RDC algorithm and how it operates. Afterwards we discuss modifications to the algorithm made to enhance compression. We describe the cascading of RDC with the Adaptive Huffman algorithm using flowcharts to illustrate their interface. We then give a description of how to operate the resulting hybrid coder using maximum compression or speed. To determine impact of enhancements, a second analysis measures performance of the new hybrid coder against the original RDC coder. To conclude the success of the thesis experiment, performance of the hybrid coder is measured against a well accepted coder called \"PKZIP v2.04.\" We then draw conclusions of experimental results and look at possible future directions.
","abstract_html":"<p>This thesis experiment is an exploration of Ross Data Coding (RDC) with several modifications intended to significantly improve compression efficiency. Experimental analysis show the RDC algorithm produces compression efficiency at a comparable level to other well known encoders with exceptionally low CPU and memory requirements. This thesis purpose is to explore how to increase its compression efficiency and further sacrifice CPU resources if needed. First, we study the algorithm for possibly modifications to enhance compression. Second, we combine the RDC algorithm with a statistical based algorithm to increase compression further. This resultant hybrid coder (RAH_S8) can optimize for maximum speed or compression depending on requirements. Through use of a parameter the user can select between maximum speed and compression. For maximum speed the hybrid algorithm uses modified RDC coding alone. For maximum compression the hybrid combines RDC coding with Adaptive Huffman coding. This thesis reviews background information of data compression as it pertains to this thesis. A preliminary analysis yields performance results of several traditional compression algorithms along with RDC coding. The analysis focuses on three different variables: compression efficiency, performance, and memory usage. This thesis then gives an overview of the original RDC algorithm and how it operates. Afterwards we discuss modifications to the algorithm made to enhance compression. We describe the cascading of RDC with the Adaptive Huffman algorithm using flowcharts to illustrate their interface. We then give a description of how to operate the resulting hybrid coder using maximum compression or speed. To determine impact of enhancements, a second analysis measures performance of the new hybrid coder against the original RDC coder. To conclude the success of the thesis experiment, performance of the hybrid coder is measured against a well accepted coder called "PKZIP v2.04." We then draw conclusions of experimental results and look at possible future directions.</p>","abstract_has_math":false,"creators":["Jenner, Wilhelm J."],"institution":null,"degree_name":"Master of Science (MS) in Computer Science","degree_level":"Thesis: EWU Only","degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":1993,"date_issued":"1993-01-01T08:00:00Z","date_published":"1993-01-01T08:00:00Z","updated_at":"2026-07-24T02:12:46Z","subjects":["Data Science","Other Computer Sciences","Theory and Algorithms"],"languages":[],"rights":["Access perpetually restricted to EWU users with an active EWU NetID"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://dc.ewu.edu/theses/877","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Jenner, Wilhelm J."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis: EWU Only"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science (MS) in Computer Science"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Data Science","Other Computer Sciences","Theory and Algorithms"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["Access perpetually restricted to EWU users with an active EWU NetID"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://dc.ewu.edu/theses/877"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This thesis experiment is an exploration of Ross Data Coding (RDC) with several modifications intended to significantly improve compression efficiency. Experimental analysis show the RDC algorithm produces compression efficiency at a comparable level to other well known encoders with exceptionally low CPU and memory requirements. This thesis purpose is to explore how to increase its compression efficiency and further sacrifice CPU resources if needed. First, we study the algorithm for possibly modifications to enhance compression. Second, we combine the RDC algorithm with a statistical based algorithm to increase compression further. This resultant hybrid coder (RAH_S8) can optimize for maximum speed or compression depending on requirements. Through use of a parameter the user can select between maximum speed and compression. For maximum speed the hybrid algorithm uses modified RDC coding alone. For maximum compression the hybrid combines RDC coding with Adaptive Huffman coding. This thesis reviews background information of data compression as it pertains to this thesis. A preliminary analysis yields performance results of several traditional compression algorithms along with RDC coding. The analysis focuses on three different variables: compression efficiency, performance, and memory usage. This thesis then gives an overview of the original RDC algorithm and how it operates. Afterwards we discuss modifications to the algorithm made to enhance compression. We describe the cascading of RDC with the Adaptive Huffman algorithm using flowcharts to illustrate their interface. We then give a description of how to operate the resulting hybrid coder using maximum compression or speed. To determine impact of enhancements, a second analysis measures performance of the new hybrid coder against the original RDC coder. To conclude the success of the thesis experiment, performance of the hybrid coder is measured against a well accepted coder called \"PKZIP v2.04.\" We then draw conclusions of experimental results and look at possible future directions.
"]},{"key":"dc:title","label":"Title","values":["Hybrid coding with enhanced RDC and Huffman compression algorithms"]}]}],"canonical_facts":{"dc:creator":["Jenner, Wilhelm J."],"dc:description.abstract":["This thesis experiment is an exploration of Ross Data Coding (RDC) with several modifications intended to significantly improve compression efficiency. Experimental analysis show the RDC algorithm produces compression efficiency at a comparable level to other well known encoders with exceptionally low CPU and memory requirements. This thesis purpose is to explore how to increase its compression efficiency and further sacrifice CPU resources if needed. First, we study the algorithm for possibly modifications to enhance compression. Second, we combine the RDC algorithm with a statistical based algorithm to increase compression further. This resultant hybrid coder (RAH_S8) can optimize for maximum speed or compression depending on requirements. Through use of a parameter the user can select between maximum speed and compression. For maximum speed the hybrid algorithm uses modified RDC coding alone. For maximum compression the hybrid combines RDC coding with Adaptive Huffman coding. This thesis reviews background information of data compression as it pertains to this thesis. A preliminary analysis yields performance results of several traditional compression algorithms along with RDC coding. The analysis focuses on three different variables: compression efficiency, performance, and memory usage. This thesis then gives an overview of the original RDC algorithm and how it operates. Afterwards we discuss modifications to the algorithm made to enhance compression. We describe the cascading of RDC with the Adaptive Huffman algorithm using flowcharts to illustrate their interface. We then give a description of how to operate the resulting hybrid coder using maximum compression or speed. To determine impact of enhancements, a second analysis measures performance of the new hybrid coder against the original RDC coder. To conclude the success of the thesis experiment, performance of the hybrid coder is measured against a well accepted coder called \"PKZIP v2.04.\" We then draw conclusions of experimental results and look at possible future directions.
"],"dc:identifier":["https://dc.ewu.edu/theses/877"],"dc:rights":["Access perpetually restricted to EWU users with an active EWU NetID"],"dc:subject":["Data Science","Other Computer Sciences","Theory and Algorithms"],"dc:title":["Hybrid coding with enhanced RDC and Huffman compression algorithms"],"thesis:degree_discipline":["Computer Science"],"thesis:degree_level":["Thesis: EWU Only"],"thesis:degree_name":["Master of Science (MS) in Computer Science"]},"updated_at":"2026-07-24T02:12:46Z"}