00796nam0-22002891i-450-99000126928040332120071112154529.00821815296000126928FED01000126928(Aleph)000126928FED0100012692820001205d1988----km-y0itay50------baengAmenabilityAlan L. T. PatersonProvidence, R.I.American Mathematical Society1988xvii, 452 p.26 cmMathematical surveys and monographs29515.2433Paterson,Alan L.T.58121ITUNINARICAUNIMARCBK990001269280403321C-46-(296399MA1MA1Amenability380060UNINA02520oam 2200565M 450 991071564560332120191121064213.9(CKB)5470000002513609(OCoLC)1065548857(OCoLC)995470000002513609(EXLCZ)99547000000251360920070221d1841 ua 0engurcn|||||||||txtrdacontentcrdamediacrrdacarrierIn Senate of the United States. Motion submitted by Mr. Crittenden, in relation to the Bill (S. 28) "To Establish a Permanent Prospective Pre-emption System in Favor of Settlers on the Public Lands, Who Shall Inhabit and Cultivate the Same, and Raise a Log-cabin Thereon." January 8, 1841. Submitted, and ordered to be printed[Washington, D.C.] :[publisher not identified],1841.1 online resource (1 page)Senate document / 26th Congress, 2nd session. Senate ;no. 54[United States congressional serial set ] ;[serial no. 376]Batch processed record: Metadata reviewed, not verified. Some fields updated by batch processes.FDLP item number not assigned.In Senate of the United States. Motion submitted by Mr. Crittenden, in relation to the Bill Improvements (Law)Land useGovernment policyLand settlementLegislative amendmentsPre-emption rights (United States)Public land salesRevenue sharingLegislative materials.lcgftImprovements (Law)Land useGovernment policy.Land settlement.Legislative amendments.Pre-emption rights (United States)Public land sales.Revenue sharing.Crittenden John J(John Jordan),1787-1863Whig (KY)1388505WYUWYUOCLCQOCLCOOCLCQBOOK9910715645603321In Senate of the United States. Motion submitted by Mr. Crittenden, in relation to the Bill (S. 28) "To Establish a Permanent Prospective Pre-emption System in Favor of Settlers on the Public Lands, Who Shall Inhabit and Cultivate the Same, and Raise a Log-cabin Thereon." January 8, 1841. Submitted, and ordered to be printed3466687UNINA05625nam 22008055 450 991091778490332120250423073149.09789819792825981979282710.1007/978-981-97-9282-5(MiAaPQ)EBC31837019(Au-PeEL)EBL31837019(CKB)37018324700041(OCoLC)1484075698(DE-He213)978-981-97-9282-5(EXLCZ)993701832470004120241214d2024 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierSpiking Neural P Systems Theory, Applications and Implementations /by Gexiang Zhang, Sergey Verlan, Tingfang Wu, Francis George C. Cabarle, Jie Xue, David Orellana-Martín, Jianping Dong, Luis Valencia-Cabrera, Mario J. Pérez-Jiménez1st ed. 2024.Singapore :Springer Nature Singapore :Imprint: Springer,2024.1 online resource (435 pages)Intelligent Technologies and Robotics Series9789819792818 9819792819 Part I. Theoretical Aspects of Spiking Neural P Systems -- Chapter 1. Fundamentals of Spiking Neural P Systems -- Chapter 2. Computational Power of Spiking Neural P Systems -- Chapter 3. Computational Complexity of Spiking Neural P Systems -- Chapter 4. Variants of Spiking Neural P Systems -- Chapter 5. Automatic Design of Spiking Neural P Systems -- Part II. Real-world Applications of Spiking Neural P Systems -- Chapter 6. Complex Optimization with Spiking Neural P Systems -- Chapter 7. Classification with Spiking Neural P Systems -- Chapter 8. Fault Diagnosis with Spiking Neural P Systems -- Chapter 9. Medical Image Processing with Spiking Neural P Systems -- Chapter 10. More Applications of Spiking Neural P Systems -- Part III. Implementations of Spiking Neural P Systems -- Chapter 11. Software Simulations of Spiking Neural P Systems -- Chapter 12. Hardware Simulations of Spiking Neural P Systems.Spiking neural P systems represent a significant advancement in the field of membrane computing, drawing inspiration from the communication patterns observed in neurons. Since their inception in 2006, these distributed and parallel neural-like computing models have gained popularity and emerged as important tools within the membrane computing area. As a key branch of the third generation of artificial neural networks, a fascinating research area of artificial intelligence, spiking neural P systems offer a captivating blend of theoretical elegance and practical utility. Their efficiency, Turing completeness, and real-life application characteristics, including interpretability and suitability for large-scale problems, have positioned them at the forefront of contemporary research in membrane computing and artificial intelligence. This state-of-the-art reference work is organized into three parts comprising twelve chapters. It thoroughly investigates the theoretical foundations, real-life applications, and implementations of spiking neural P systems. From fundamental principles to computational power and complexity, the theoretical aspects are explored, laying the groundwork for understanding their practical applications. Real-life applications span a diverse range of domains, including complex optimization, classification, fault diagnosis, medical image processing, information fusion, cryptography, and robot control. Additionally, the book discusses several software and hardware implementations that provide valuable insights into the practical deployment of spiking neural P systems. As the rapid development of spiking neural P systems continues to unfold, there is an increasing demand for a systematic and comprehensive summary of their capabilities and applications. This work serves as an invaluable resource for researchers, scholars, and practitioners interested in the theoretical underpinnings, algorithms, and practical implementation of artificial intelligence and membrane computing.Computational intelligenceComputational complexityArtificial intelligenceMachine learningComputer scienceComputational IntelligenceComputational ComplexityArtificial IntelligenceMachine LearningTheory and Algorithms for Application DomainsModels of ComputationComputational intelligence.Computational complexity.Artificial intelligence.Machine learning.Computer science.Computational Intelligence.Computational Complexity.Artificial Intelligence.Machine Learning.Theory and Algorithms for Application Domains.Models of Computation.006.32Zhang Gexiang933282Verlan Sergey1780021Wu Tingfang1780022Cabarle Francis George C1780023Xue Jie1780024Orellana-Martín David1780025Dong Jianping1780026Valencia-Cabrera Luis1780027Pérez-Jiménez Mario J1757463MiAaPQMiAaPQMiAaPQBOOK9910917784903321Spiking Neural P Systems4303677UNINA