Relevant bibliographies by topics / Pattern-matching engine

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Academic literature on the topic 'Pattern-matching engine'

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Published: 10 January 2023

Last updated: 28 January 2023

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Journal articles on the topic "Pattern-matching engine"

Peng, Zhan, Yuping Wang, and Wei Yue. "A Fast Engine for Multi-String Pattern Matching." International Journal of Pattern Recognition and Artificial Intelligence 31, no. 12 (September 17, 2017): 1750039. http://dx.doi.org/10.1142/s0218001417500392.

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Multi-string matching (MSM) is a core technique searching a text string for all occurrences of some string patterns. It is widely used in many applications. However, as the number of string patterns increases, most of the existing algorithms suffer from two issues: the long matching time, and the high memory consumption. To address these issues, in this paper, a fast matching engine is proposed for large-scale string matching problems. Our engine includes a filter module and a verification module. The filter module is based on several bitmaps which are responsible for quickly filtering out the invalid positions in the text, while for each potential matched position, the verification module confirms true pattern occurrence. In particular, we design a compact data structure called Adaptive Matching Tree (AMT) for the verification module, in which each tree node only saves some pattern fragments of the whole pattern set and the inner structure of each tree node is chosen adaptively according to the features of the corresponding pattern fragments. This makes the engine time and space efficient. The experiments indicate that, our matching engine performs better than the compared algorithms, especially for large pattern sets.

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Ko, Kwang-Man, and Hong-Jin Park. "Development of the Pattern Matching Engine using Regular Expression." Journal of the Korea Contents Association 8, no. 2 (February 28, 2008): 33–40. http://dx.doi.org/10.5392/jkca.2008.8.2.033.

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LIU, Wei, Yuan-bo GUO, and Peng HUANG. "Pattern matching engine based on multi-dimensional bloom filters." Journal of Computer Applications 31, no. 1 (March 21, 2011): 107–9. http://dx.doi.org/10.3724/sp.j.1087.2011.00107.

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Chen, Z., Y. Zhang, Z. Chen, and A. Delis. "A Digest and Pattern Matching-Based Intrusion Detection Engine." Computer Journal 52, no. 6 (April 15, 2009): 699–723. http://dx.doi.org/10.1093/comjnl/bxp026.

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Tran, Thinh Ngoc. "CPM: CUCKOO-BASED PATTERN MATCHING APPLIED FOR NIDS." Science and Technology Development Journal 14, no. 2 (June 30, 2011): 53–61. http://dx.doi.org/10.32508/stdj.v14i2.1909.

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This paper describes the Cuckoo-based Pattern Matching (CPM) engine which based on a recently developed hashing algorithm called Cuckoo Hashing. We implemented the improved parallel Cuckoo Hashing suitable for hardware-based multi-pattern matching with arbitrary length. CPM is scalable with multi-character per clock cycle to sustain higher throughput rates with lower hardware resources. With the power of massively parallel processing, the speedup of CPM is up to 128X as compared with serial Cuckoo implementation. Compared to other hardware systems, CPM is far better in performance and save 30% of the area compared with the best system.

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THINH, Tran Ngoc, Surin KITTITORNKUN, and Shigenori TOMIYAMA. "PAMELA: Pattern Matching Engine with Limited-Time Update for NIDS/NIPS." IEICE Transactions on Information and Systems E92-D, no. 5 (2009): 1049–61. http://dx.doi.org/10.1587/transinf.e92.d.1049.

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Hieu, Tran Trung, and Tran Ngoc Thinh. "mDFA: A Memory Efficient DFA-Based Pattern Matching Engine on FPGA." Wireless Personal Communications 78, no. 4 (September 2, 2014): 1833–47. http://dx.doi.org/10.1007/s11277-014-2047-x.

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Huang, Yu Hsiu, Richard Chun Hung Lin, Ying Chih Lin, and Cheng Yi Lin. "GPU Computation for Online Realtime Multi-Pattern Matching." Applied Mechanics and Materials 284-287 (January 2013): 3428–32. http://dx.doi.org/10.4028/www.scientific.net/amm.284-287.3428.

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Most applications of traditional full-text search, e.g., webpage search, are offline which exploit text search engine to preview the texts and set up related index. However, applications of online realtime full-text search, e.g., network Intrusion detection and prevention systems (IDPS) are too hard to implementation by using commodity hardware. They are expensive and inflexible for more and more occurrences of new virus patterns and the text cannot be previewed and the search must be complete realtime online. Additionally, IDPS needs multi-pattern matching, and then malicious packets can be removed immediately from normal ones without degrading the network performance. Considering the problem of realtime multi-pattern matching, we implement two sequential algorithms, Wu-Manber and Aho-Corasick, respectively over GPU parallel computation platform. Both pattern matching algorithms are quite suitable for the cases with a large amount of patterns. In addition, they are also easier extendable over GPU parallel computation platform to satisfy realtime requirement. Our experimental results show that the throughput of GPU implementation is about five to seven times faster than CPU. Therefore, pattern matching over GPU offers an attractive solution of IDPS to speed up malicious packets detection among the normal traffic by considering the lower cost, easy expansion and better performance.

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Hoeltzel, D. A., and Wei-Hua Chieng. "Pattern Matching Synthesis as an Automated Approach to Mechanism Design." Journal of Mechanical Design 112, no. 2 (June 1, 1990): 190–99. http://dx.doi.org/10.1115/1.2912592.

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A new knowledge-based approach for the synthesis of mechanisms, referred to as Pattern Matching Synthesis, has been developed based on a combination of committee machine and Hopfield neutral network models of pattern classification and matching applied to coupler curves. Computational tests performed on a dimensionally-parameterized four bar mechanism have yielded 15 distinct coupler curve groups (patterns) from a total of 356 generated coupler curves. This innovative approach represents a first step toward the automation of mapping structure-to-function in mechanism design based on the application of artificial intelligence programing techniques. Demonstrative examples of its application to “real-world” mechanism synthesis problems, including the design and evaluation of a two-stroke pump mechanism and the redesign of a variable-stroke engine mechanism have been included, establishing its viability for creative mechanism synthesis.

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Jing, Zhou. "Research on the Shift Strategy for the Traction Vehicle with Automatic Transmission." E3S Web of Conferences 198 (2020): 03029. http://dx.doi.org/10.1051/e3sconf/202019803029.

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Firstly, according to the working characteristic diagram of engine and hydraulic torque converter, the matching working point is found. On this basis, the theoretical model of gear shifting law is derived when the engine and the hydraulic torque converter work together by taking the acceleration of adjacent two gears equal as the shift point. Finally, the theoretical model is simulated, the shift pattern diagram of tractor automatic transmission is obtained and the shift pattern diagram is analyzed, and the results are of important reference value for further study of shift delay and other characteristics.

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Dissertations / Theses on the topic "Pattern-matching engine"

Lee, Y. H. "Gas turbine engine health monitoring by fault pattern matching method." Thesis, Cranfield University, 1998. http://dspace.lib.cranfield.ac.uk/handle/1826/10714.

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The gas turbine engine has a wide range of applications, these include industrial and aerospace applications on locomotive, ferry, compressor and power generation, and the most popular application will be for the air transportation. The application for air transportation including military and commercial aircraft is highly sensitive to safety concerns. The engine health monitoring system plays a major role for addressing this concern, a good engine monitoring system will not only to provide immediate and correct information to the engine user but also provide useful information for managing the maintenance activities. Without a reliable performance diagnosis module involved, there will be not possible to build a good health monitoring system. There are many methodologies had been proposed and studied during past three decades, and yet still struggling to search for some good techniques to handle instrumentation errors. In order to develop a reliable engine performance diagnosis technique, a fully understanding and proper handling of the instrumentation is essential. A engine performance fault pattern matching method has been proposed and developed in this study, two fault libraries contains a complete defined set of 51963 faults was created by using a newly serviced fighter engine component data. This pattern matching system had been verified by different approaches, such as compares with linear and nonlinear diagnosis results and compares with performance sensitivity analysis results by using LTF program engine data. The outcomes from the verications indicate an encouraging result for further exploring this method. In conclusion, this research has not only propose a feasible performance diagnosis techniques, but also developed and verified through different kind of approaches for this techniques. In addition to that, by proper manipulating the created fault library, a possible new tool for analyzing the application of instruments' implementation was discovered. The author believes there will be more to study by using this created fault pattern library. For instance, this fault pattern library can be treated as a very good initial training sets for neural networking to develop a neural diagnosis technique. This study has put a new milestone for further exploring gas turbine diagnosis technique by using fault pattern related methods.

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Ho, Johnny Tsung Lin. "PERG-Rx : an FPGA-based pattern-matching engine with limited regular expression support for large pattern databases." Thesis, University of British Columbia, 2009. http://hdl.handle.net/2429/12921.

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Pattern-matching is a fundamental technique found in applications like a network intrusion detection system (NIDS) and antivirus. By comparing an input data stream against a set of predefined byte-string patterns, malicious activities can be detected. Due to the increasing pattern database size, hardware engines are frequently being used to accelerate pattern-matching because software-based solution can no longer keep up. This thesis presents PERG, a FPGA-based pattern-matching engine targeted for the large pattern database found in Clam AntiVirus (ClamAV). Previous hardware pattern-matching engines have targeted the Snort database used in NIDS. PERG is the first hardware pattern-matching engine designed for the ClamAV pattern database, which is several times larger than Snort in both the number of patterns and the range of pattern lengths. Among hash-based pattern-matching hardware, PERG is the first to integrate limited regular-expression support. In ClamAV, this feature is needed for polymorphic virus detection. Finally among hash-based hardware pattern-matching engines, PERG is the first to implement Bloomier filters. With Bloomier filters, the process of exact matching to verify a false positive in PERG is much simpler and faster than other hash-based pattern-matching engines which use traditional Bloom filters. To reduce hardware resources, PERG uses a pattern compiler to transform the pattern database into an optimized hardware implementation. The compiler packs as many pattern strings as possible into each Bloomier filter unit, a hardware module, by consolidating several different pattern lengths into the same filter unit. To further save on hardware resources, limited regular-expression support for wildcard patterns is provided using a lossy scheme, which trades off a slight increase in false-positive probability to gain significant savings in hardware resources. False-negative probability in PERG remains zero. Using the ClamAV antivirus database, PERG fits 84,387 patterns containing over 8,645,488 characters into a single modest FPGA chip with a small (4 MB) off-chip memory. It uses just 26 filter units, resulting in roughly 24.7x improved density (characters per memory bit) compared to the next-best NIDS pattern-matching engine which fits only 1/126th the characters. PERG can scan at roughly 170MB/s and match the speed of most network or disk interfaces.

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Chang, Ching-Liang, and 張清諒. "The Design and Implementation of a Perl Compatible Regular Expression Pattern Matching Engine with Pipeline Architecture using FPGAs." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/66585314611629707358.

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碩士
國立臺灣大學
電機工程學研究所
96
A regular expression is powerful to describe signature patterns used in an Intrusion Detection System (IDS). This paper focuses on how to employ a pipeline architecture to NFA-based hardware implementations in order to increase the system performance. We propose a comparator that shares comparison operators including the ASCII decoder, the static pattern matching, and the char classes, and then we partition the comparator into two stages. As a result, we apply a three-stage pipeline to our Perl compatible regular expression pattern matching engine (PCRE engine) including a two-stage pipeline comparator and a one-stage NFA-based pattern recognizer. In addition, we can easily implement Caret meta-character (means the beginning of a string) when using the three-stage pipeline architecture. Finally, experimental results show that the proposed three-stage PCRE engine has a throughput of 2.4 Gbps as compared with the 1.8 Gpbs of the original PCRE engine in an Altera DE2 platform. This means that the proposed approach can have 30% performance increase in the current implementation with respect to the non-pipeline one.

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Ieong, Tou, and 楊滔. "A Hardware Accelerated Packet Processing Platform with Memory-Efficient Pattern Matching Engines." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/92039389615681903932.

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碩士
國立臺灣大學
電機工程學研究所
96
A Network Intrusion Detection System (NIDS) collects known signatures of network threats and carries out pattern matching between packet payload and signatures to protect our network. Signatures are often represented by regular expressions and pattern matching occupied most of computing time in an NIDS. To keep the network operating at full speed, hardware accelerators are used in pattern matching. In this thesis, we extended the History based Counting Finite Automaton (H-cFA) to Bitmap H-cFA, which used a bitmap data structure to store the "walked" states and recorded the repeat count in a history buffer to reduce the total number of states in finite automata. Bitmap H-cFA not only kept the low memory characteristic but also provided more support in regular expression formats, making a more generalized pattern matching engine. We also presented a hardware accelerated packet processing platform, which allowed pattern matching intellectual properties (IPs) to be tested in FPGA. The proposed packet processing platform consisted of a packet payload extractor and a TCP packet header parser. It could easily be integrated with a pattern matching engine to test the system. We implemented the proposed packet processing platform and the pattern matching engine in a Xilinx ML405 FPGA development board and obtained a processing throughput of 231 Mbps.

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Ieong, Tou. "A Hardware Accelerated Packet Processing Platform with Memory-Efficient Pattern Matching Engines." 2008. http://www.cetd.com.tw/ec/thesisdetail.aspx?etdun=U0001-0808200816551100.

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Rasool, Raihan Ur. "CyberPulse: A Security Framework for Software-Defined Networks." Thesis, 2020. https://vuir.vu.edu.au/42172/.

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Software-Defined Networking (SDN) technology provides a new perspective in traditional network management by separating infrastructure plane from the control plane which facilitates a higher level of programmability and management. While centralized control provides lucrative benefits, the control channel becomes a bottleneck and home to numerous attacks. We conduct a detailed study and find that crossfire Link Flooding Attacks (LFA) are one of the most lethal attacks for SDN due to the utilization of low-rate traffic and persistent attacking nature. LFAs can be launched by the malicious adversaries to congest the control plane with low-rate traffic which can obstruct the flow rule installation and can ultimately bring down the whole network. Similarly, the adversary can employ bots to generate low-rate traffic to congest the control channel, and ultimately bring down the control plane and data plane connection causing service disruption. We present a systematic and comparative study on the vulnerabilities of LFAs on all the SDN planes, elaborate in detail the LFA types, techniques, and their behavior in all the variant of SDN. We then illustrate the importance of a defense mechanism employing a distributed strategy against LFAs and propose a Machine Learning (ML) based framework namely CyberPulse. Its detailed design, components, and their interaction, working principles, implementation, and in-depth evaluation are presented subsequently. This research presents a novel approach to write anomaly patterns and makes a significant contribution by developing a pattern-matching engine as the first line of defense against known attacks at a line-speed. The second important contribution is the effective detection and mitigation of LFAs in SDN through deep learning techniques. We perform twofold experiments to classify and mitigate LFAs. In the initial experimental setup, we utilize Artificial Neural Networks backward propagation technique to effectively classify the incoming traffic. In the second set of experiments, we employ a holistic approach in which CyberPulse demonstrates algorithm agnostic behavior and employs a pre-trained ML repository for precise classification. As an important scientific contribution, CyberPulse framework has been developed ground up using modern software engineering principles and hence provides very limited bandwidth and computational overhead. It has several useful features such as large-scale network-level monitoring, real-time network status information, and support for a wide variety of ML algorithms. An extensive evaluation is performed using Floodlight open-source controller which shows that CyberPulse offers limited bandwidth and computational overhead and proactively detect and defend against LFA in real-time. This thesis contributes to the state-of-the-art by presenting a novel framework for the defense, detection, and mitigation of LFA in SDN by utilizing ML-based classification techniques. Existing solutions in the area mandate complex hardware for detection and defense, but our presented solution offers a unique advantage in the sense that it operates on real-time traffic scenario as well as it utilizes multiple ML classification algorithms for LFA traffic classification without necessitating complex and expensive hardware. In the future, we plan to implement it on a large testbed and extend it by training on multiple datasets for multiple types of attacks.

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Book chapters on the topic "Pattern-matching engine"

Krause, Christian, Daniel Johannsen, Radwan Deeb, Kai-Uwe Sattler, David Knacker, and Anton Niadzelka. "An SQL-Based Query Language and Engine for Graph Pattern Matching." In Graph Transformation, 153–69. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-40530-8_10.

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Ryabinin, Konstantin, Konstantin Belousov, and Roman Chumakov. "Ontology-Driven Data Mining Platform for Fuzzy Classification of Mental Maps." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2021. http://dx.doi.org/10.3233/faia210208.

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Mental maps are valuable material for Digital Humanities research since they represent a summary of humans spatial experience reflected in their minds. Contributing to this research, we developed a high-level Web-based software platform that allows to collect drawings of mental maps and to perform corresponding data mining and fuzzy classification. The novelty of the proposed platform is the ontology-based integration of mental maps drawing engine and data mining engine, wherein all the essential steps of data mining, including data acquisition, transformation, fuzzy classification, and visual analytics are driven by ontologies. The platform consists of a high-level graphical editor to draw maps and a data flow diagram editor to define the data mining pipeline. The operators available to construct this pipeline are described by ontology, which ensures the platform’s extensibility on the knowledge base level. Thereby, the platform created can be used not only for Digital Humanities research but also for testing and evaluation of new data mining and fuzzy classification methods. Currently, we have evaluated weighted fuzzy pattern matching for mental maps fuzzy classification and confirmed the reasonable performance of this method.

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Ali Yüksel, Kamer. "Gestural Interaction with Mobile Devices Based on Magnetic Field." In Advances in Wireless Technologies and Telecommunication, 203–22. IGI Global, 2014. http://dx.doi.org/10.4018/978-1-4666-4446-5.ch011.

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The theory of around device interaction (ADI) has recently gained a lot of attention in the field of human computer interaction (HCI). As an alternative to the classic data entry methods, such as keypads and touch screens, ADI founds a 3D user interface that extends to the peripheral area of a device. In this chapter, the authors introduce a revolutionary interaction framework that is based on the idea of ADI. The proposed method constitutes a touchless data entry system that is based on the interaction between the magnetic fields around a device and a properly shaped magnet. The magnetic field that surrounds the device is generated by a magnetic sensor (compass) that is embedded in the new generation of mobile phones such as Apple’s iPhone 3GS and 4G, and Google’s Nexus one. The user movements of the properly shaped magnet in front of the device, then, deforms the sensor’s original magnetic field pattern whereby we can constitute a new means of communication between the user and the device. Thus, the magnetic field encompassing the device plays the role of a communication channel and encodes the hand-movement patterns of the user into temporal changes of the sensor’s magnetic field. In the back-end of the communication, an engine samples the momentary status of the field during a trial and recognizes the user’s pattern by matching it against some pre-recorded templates. The proposed method has been tested in a variety of applications such as handwriting recognition, user authentication, gesture recognition, and some entertainment applications. The experimental results show that the proposed interface not only elevates the convenience of user-device interactions, but also shows very promising accuracies in a wide range of applications requiring user interactions.

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Chaudhry, Junaid Ahsenali. "Automatic Self Healing Using Immune Systems." In Encyclopedia of Multimedia Technology and Networking, Second Edition, 105–12. IGI Global, 2009. http://dx.doi.org/10.4018/978-1-60566-014-1.ch015.

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The networking technologies are moving very fast in pursuit of optimum performance, which has triggered the importance of non-conventional computing methods. In the modern world of pervasive business systems, time is money. The more the system fulfills the needs of the requesting user, the more revenue the business will generate. The modern world is service-oriented, and therefore, providing customers with reliable and fast service delivery is of paramount importance. In this article we present a scheme to increase the reliability of business systems. The arrival of ubiquitous computing has triggered the need previously mentioned even further, and people hold high exceptions from this technology. In Morikawa (2004), the authors characterize the vision of ubiquitous computing into two categories: “3C everywhere and physical interaction.” 3C consists of “computing everywhere,” “content everywhere,” and “connectivity everywhere.” “Physical interaction” connects the hidden world of ubiquitous sensors with the real world. This wide area of coverage and high scalability makes a ubiquitous system quite fragile toward not only external threats, but internal malfunctioning too. With the high probability of “abnormal behavior” it is more important to have knowledge of fault and its root causes. As described in Yau, Wang, and Karim (2002), application failures are like diseases, and there can be many types of faults with matching symptoms, thus fault localization and categorization are very important. Unlike in Hung et al. (2005) and Steglich and Arbanowski (2004), we cannot categorize all abnormal functionalities into fault tolerance or (re)configuration domains simply because faults do not have any predefined pattern; rather we have to find those pattern. Moreover, as in Steglich and Arbanowski (2004) the “without foresight” type of repair in ubiquitous systems is desired. The conventional FCAPS (Fault, Configuration, Accounting, Performance, Security), network management model categorizes management functions in one group, but we argue that categorizing management functions into different segment is mandatory in self management paradigms. Since in highly dynamic and always available very wide area networks, one fault can be atomic (caused because of one atomic reason) or it can be a set of many faults (caused because of many atomic or related reasons). It is often a good practice to break the problem into smaller atomic problems and then solve them (Chaudhry, Park, & Hong, 2006). If we classify all different types of faults (atomic, related, and composite) into one fault management category, the results would not be satisfactory, nor would the system be able to recover from the “abnormal state” well. Since the side effects of system stability and self healing actions are not yet known (Yau et al., 2002), we cannot afford to assume that running self management modules along with functional modules of the core system will not have a negative effect on the system performance. For example, if the system is working properly, there is no need for fault management modules to be active. Lastly, instead of having a fault-centric approach, we should have a recovery-centric approach because of our objective that is to increase the system availability In this article we present autonomic self healing engine (ASHE) architecture for ubiquitous smart systems. We identify the problem context through artificial immune system techniques and vaccinate (deploy solution to) the system through dynamically composed applications. The services involved in the service composition process may or may not be related, but when they are composed into an application they behave in a way it is specified in their composition scheme. The vaccines are dissolved to liberate the system resources (because they take the system’s own resources to recover it) after the system recovery. When the system is running in a normal state, all self management modules are turned off except context awareness and self optimization. These two are always on to monitor and optimize the system respectively.

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Conference papers on the topic "Pattern-matching engine"

Hao, Kongzhang, Zhengyi Yang, Longbin Lai, Zhengmin Lai, Xin Jin, and Xuemin Lin. "PatMat: A Distributed Pattern Matching Engine with Cypher." In CIKM '19: The 28th ACM International Conference on Information and Knowledge Management. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3357384.3357840.

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Yadav, Meeta, Ashwini Venkatachaliah, and Paul D. Franzon. "Hardware Architecture of a Parallel Pattern Matching Engine." In 2007 IEEE International Symposium on Circuits and Systems. IEEE, 2007. http://dx.doi.org/10.1109/iscas.2007.378482.

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Zhu, Wenjun, Harry Chang, Yang Hong, Xiang Wang, Geoff Langdale, Kun Qiu, and Mingyi Zhang. "Hyperverse: A High Throughput Pattern Matching Engine for Metaverse." In 2022 IEEE 42nd International Conference on Distributed Computing Systems Workshops (ICDCSW). IEEE, 2022. http://dx.doi.org/10.1109/icdcsw56584.2022.00054.

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Zha, Xinyan, Daniele Paolo Scarpazza, and Sartaj Sahni. "Highly compressed multi-pattern string matching on the cell broadband engine." In 2011 IEEE Symposium on Computers and Communications (ISCC). IEEE, 2011. http://dx.doi.org/10.1109/iscc.2011.5983850.

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Tran Trung Hieu and Ngoc Thinh Tran. "A memory efficient FPGA-based pattern matching engine for stateful NIDS." In 2013 Fifth International Conference on Ubiquitous and Future Networks (ICUFN). IEEE, 2013. http://dx.doi.org/10.1109/icufn.2013.6614821.

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Piyachon, Piti, and Yan Luo. "Design of high performance pattern matching engine through compact deterministic finite automata." In the 45th annual conference. New York, New York, USA: ACM Press, 2008. http://dx.doi.org/10.1145/1391469.1391685.

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Ho, Johnny Tsung Lin, and Guy G. F. Lemieux. "PERG: A scalable FPGA-based pattern-matching engine with consolidated Bloomier filters." In 2008 International Conference on Field-Programmable Technology (FPT). IEEE, 2008. http://dx.doi.org/10.1109/fpt.2008.4762368.

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Kawanaka, Yosuke, Shin'ichi Wakabayashi, and Shinobu Nagayama. "A systolic regular expression pattern matching engine and its application to network intrusion detection." In 2008 International Conference on Field-Programmable Technology (FPT). IEEE, 2008. http://dx.doi.org/10.1109/fpt.2008.4762402.

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Lee, Y. H., and R. Singh. "Health Monitoring of Turbine Engine Gas Path Components and Measurement Instruments." In ASME 1996 International Gas Turbine and Aeroengine Congress and Exhibition. American Society of Mechanical Engineers, 1996. http://dx.doi.org/10.1115/96-gt-242.

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A performance simulation program has been used to simulate deteriorated performance of a new augmented turbofan engine developed for fighter aircraft and generate a fault pattern library. This fault pattern library forms a basis for both understanding degradation trends of engine usage and in developing an engine health monitoring system. An efficient health monitoring method is proposed to identify the engine faults along with measurement uncertainties and faulty instruments, and to reduce false alarms. A pattern matching method is used to discriminate the engine faults by matching the measurement patterns throughout the fault pattern library. The comparison of this approach to conventional gas path analysis has demonstrated that this approach has comparable ability to monitor engine gas path performance degradation, and provides some capability to handle measurement uncertainties and faults. It also provides a good base for future capability in conjunction with other engine inspection and/or monitoring methods.

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van Lunteren, Jan, and Ton Engbersen. "High-performance pattern-matching engine for intrusion detection: A new approach for fast programmable accelerators." In 2005 IEEE Hot Chips XVII Symposium (HCS). IEEE, 2005. http://dx.doi.org/10.1109/hotchips.2005.7476583.

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