@article{MTMT:30901556,
	title = {Heat conduction-based methodology for nonlinear soft tissue deformation},
	url = {https://m2.mtmt.hu/api/publication/30901556},
	author = {Zhang, Jinao and Shin, Jaehyun and Zhong, Yongmin and Oetomo, Denny and Gu, Chengfan},
	doi = {10.1007/s12008-018-0486-4},
	journal-iso = {IJIDEM},
	journal = {INTERNATIONAL JOURNAL ON INTERACTIVE DESIGN AND MANUFACTURING},
	volume = {13},
	unique-id = {30901556},
	issn = {1955-2513},
	abstract = {Modelling of interactions of soft tissues with surgical tools is a fundamental issue in interactive surgical simulation. This paper presents a new methodology for modelling of nonlinear characteristics of soft tissue deformation for interactive surgical simulation. The proposed methodology formulates soft tissue deformation as a process of energy propagation; the mechanical load applied to soft tissues to cause deformation is treated as the equivalent thermal energy according to the conservation law of energy and further distributed among masses of soft tissues in the manner of heat conduction. Heat conduction of mechanical load and non-rigid mechanics of motion are combined to conduct soft tissue deformation. To obtain real-time computational performance, cellular neural networks are developed for both propagation of mechanical load and non-rigid mechanical dynamics, leading to novel neural network models embedded with deformation mechanics and physical dynamics for interactive soft tissue simulation. Real-time force interaction is also achieved with an integration of a haptic device via force input, soft tissue deformation, and force feedback. Simulations and experimental results demonstrate the proposed methodology exhibits the typical mechanical behaviour of soft tissues and accepts nonlinear soft tissue deformation. It can also accommodate isotropic and homogeneous, anisotropic, and heterogeneous materials by a simple modification of thermal conductivity values of mass points.},
	keywords = {CELLULAR NEURAL NETWORKS; Real-time systems; Soft tissue deformation; Surgical simulation; Force interaction},
	year = {2019},
	eissn = {1955-2505},
	pages = {147-161},
	orcid-numbers = {Zhang, Jinao/0000-0002-1994-8374}
}

@article{MTMT:30901555,
	title = {Neural dynamics-based Poisson propagation for deformable modelling},
	url = {https://m2.mtmt.hu/api/publication/30901555},
	author = {Zhang, Jinao and Zhong, Yongmin and Smith, Julian and Gu, Chengfan},
	doi = {10.1007/s00521-017-3132-3},
	journal-iso = {NEURAL COMPUT APPL},
	journal = {NEURAL COMPUTING & APPLICATIONS},
	volume = {31},
	unique-id = {30901555},
	issn = {0941-0643},
	abstract = {This paper presents a new methodology from the standpoint of energy propagation for real-time and nonlinear modelling of deformable objects. It formulates the deformation process of a soft object as a process of energy propagation, in which the mechanical load applied to the object to cause deformation is viewed as the equivalent potential energy based on the law of conservation of energy and is further propagated among masses of the object based on the nonlinear Poisson propagation. Poisson propagation of mechanical load in conjunction with non-rigid mechanics of motion is developed to govern the dynamics of soft object deformation. Further, these two governing processes are modelled with cellular neural networks to achieve real-time computational performance. A prototype simulation system with a haptic device is implemented for real-time simulation of deformable objects with haptic feedback. Simulations, experiments as well as comparisons demonstrate that the proposed methodology exhibits nonlinear force-displacement relationship, capable of modelling large-range deformation. It can also accommodate homogeneous, anisotropic and heterogeneous materials by simply changing the constitutive coefficient value of mass points.},
	keywords = {Poisson equation; CELLULAR NEURAL NETWORKS; Nonlinear deformation; Real-time performance; deformable objects},
	year = {2019},
	eissn = {1433-3058},
	pages = {1091-1101},
	orcid-numbers = {Zhang, Jinao/0000-0002-1994-8374; Zhong, Yongmin/0000-0002-0105-9296}
}

@article{MTMT:31568951,
	title = {Neural network methodology for real-time modelling of bio-heat transfer during thermo-therapeutic applications},
	url = {https://m2.mtmt.hu/api/publication/31568951},
	author = {Zhang, Jinao and Chauhan, Sunita},
	doi = {10.1016/j.artmed.2019.101728},
	journal-iso = {ARTIF INTELL MED},
	journal = {ARTIFICIAL INTELLIGENCE IN MEDICINE},
	volume = {101},
	unique-id = {31568951},
	issn = {0933-3657},
	abstract = {Real-time simulation of bio-heat transfer can improve surgical feedback in thermo-therapeutic treatment, leading to technical innovations to surgical process and improvements to patient outcomes; however, it is challenging to achieve real-time computational performance by conventional methods. This paper presents a cellular neural network (CNN) methodology for fast and real-time modelling of bio-heat transfer with medical applications in thermo-therapeutic treatment. It formulates nonlinear dynamics of the bio-heat transfer process and spatially discretised bio-heat transfer equation as the nonlinear neural dynamics and local neural connectivity of CNN, respectively. The proposed CNN methodology considers three-dimensional (3-D) volumetric bio-heat transfer behaviour in tissue and applies the concept of control volumes for discretisation of the Pennes bio-heat transfer equation on 3-D irregular grids, leading to novel neural network models embedded with bio-heat transfer mechanism for computation of tissue temperature and associated thermal dose. Simulations and comparative analyses demonstrate that the proposed CNN models can achieve good agreement with the commercial finite element analysis package, ABAQUS/CAE, in numerical accuracy and reduce computation time by 304 and 772.86 times compared to those of with and without ABAQUS parallel execution, far exceeding the computational performance of the commercial finite element codes. The medical application is demonstrated using a high-intensity focused ultrasound (HIFU)-based thermal ablation of hepatic cancer for prediction of tissue temperature and estimation of thermal dose.},
	keywords = {CELLULAR NEURAL NETWORKS; Real-time computation; Pennes bio-heat transfer equation; Thermo-therapeutic treatment},
	year = {2019},
	eissn = {1873-2860},
	orcid-numbers = {Zhang, Jinao/0000-0002-1994-8374}
}

@article{MTMT:30901539,
	title = {Neural network modelling of soft tissue deformation for surgical simulation},
	url = {https://m2.mtmt.hu/api/publication/30901539},
	author = {Zhang, Jinao and Zhong, Yongmin and Gu, Chengfan},
	doi = {10.1016/j.artmed.2018.11.001},
	journal-iso = {ARTIF INTELL MED},
	journal = {ARTIFICIAL INTELLIGENCE IN MEDICINE},
	volume = {97},
	unique-id = {30901539},
	issn = {0933-3657},
	abstract = {This paper presents a new neural network methodology for modelling of soft tissue deformation for surgical simulation. The proposed methodology formulates soft tissue deformation and its dynamics as the neural propagation and dynamics of cellular neural networks for real-time, realistic, and stable simulation of soft tissue deformation. It develops two cellular neural network models; based on the bioelectric propagation of biological tissues and principles of continuum mechanics, one cellular neural network model is developed for propagation and distribution of mechanical load in soft tissues; based on non-rigid mechanics of motion in continuum mechanics, the other cellular neural network model is developed for governing model dynamics of soft tissue deformation. The proposed methodology not only has computational advantage due to the collective and simultaneous activities of neural cells to satisfy the real-time computational requirement of surgical simulation, but also it achieves physical realism of soft tissue deformation according to the bioelectric propagation manner of mechanical load via dynamic neural activities. Furthermore, the proposed methodology also provides stable model dynamics for soft tissue deformation via the nonlinear property of the cellular neural network. Interactive soft tissue deformation with haptic feedback is achieved via a haptic device. Simulations and experimental results show the proposed methodology exhibits the nonlinear force-displacement relationship and associated nonlinear deformation of soft tissues. Furthermore, not only isotropic and homogeneous but also anisotropic and heterogeneous materials can be modelled via a simple modification of electrical conductivity. values of mass points.},
	keywords = {Cellular neural network; Force feedback; Soft tissue deformation; Real-time performance; Surgical simulation},
	year = {2019},
	eissn = {1873-2860},
	pages = {61-70},
	orcid-numbers = {Zhang, Jinao/0000-0002-1994-8374}
}

@article{MTMT:30462751,
	title = {Neural Networks-Based Computational Modeling of Bilinear Control Systems for Conservation Laws: Application to the Control of Cogeneration},
	url = {https://m2.mtmt.hu/api/publication/30462751},
	author = {Danciu, Daniela and Popescu, Dan and Bobasu, Eugen},
	doi = {10.1109/TIA.2018.2855171},
	journal-iso = {IEEE T IND APPL},
	journal = {IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS},
	volume = {54},
	unique-id = {30462751},
	issn = {0093-9994},
	abstract = {This paper considers the computational modeling of the class of bilinear control systems for hyperbolic conservation laws with nonstandard boundary conditions. These systems arise from (control) engineering applications of systems displaying propagation phenomena, i.e., integrating steam, water, and gas pipes. The aim of this paper is achieved by means of a systematic computational procedure previously introduced and adapted here for the class of systems under consideration. The procedure, based on a convergent Method of Lines ensures the convergence of the approximate numerical solution and also the preservation of the basic properties of the "true" solution as well as its Lyapunov stability. Thus, the approximate computational model allows numerical quantitative and qualitative analysis relevant to a specific problem. The computational efficiency of the procedure is ensured by its implementation based on some, possibly massively, parallel-structured devices belonging to the Artificial Intelligence field-the cell-based recurrent neural networks. As a case study, we consider a control system occurring in the cogeneration process (combined heat and electricity generation). A comparison between the results of the qualitative analysis and those of the numerical simulations demonstrates the correctness and effectiveness of the computational procedure for the dynamics and transients analysis. The paper ends with some conclusions and a list of open problems.},
	keywords = {cogeneration; Computational modeling; Cellular neural networks (CNNs); conservation laws; Bilinear control system; heat and electricity generation process; hyperbolic partial differential equations (hPDEs); method of lines (MoL)},
	year = {2018},
	eissn = {1939-9367},
	pages = {6498-6507},
	orcid-numbers = {Danciu, Daniela/0000-0002-3854-2986; Popescu, Dan/0000-0002-6725-0050}
}

@article{MTMT:30462750,
	title = {Soft tissue deformation modelling through neural dynamics-based reaction-diffusion mechanics},
	url = {https://m2.mtmt.hu/api/publication/30462750},
	author = {Zhang, Jinao and Zhong, Yongmin and Gu, Chengfan},
	doi = {10.1007/s11517-018-1849-5},
	journal-iso = {MED BIOL ENG COMPUT},
	journal = {MEDICAL AND BIOLOGICAL ENGINEERING AND COMPUTING},
	volume = {56},
	unique-id = {30462750},
	issn = {0140-0118},
	abstract = {Soft tissue deformation modelling forms the basis of development of surgical simulation, surgical planning and robotic-assisted minimally invasive surgery. This paper presents a new methodology for modelling of soft tissue deformation based on reaction-diffusion mechanics via neural dynamics. The potential energy stored in soft tissues due to a mechanical load to deform tissues away from their rest state is treated as the equivalent transmembrane potential energy, and it is distributed in the tissue masses in the manner of reaction-diffusion propagation of nonlinear electrical waves. The reaction-diffusion propagation of mechanical potential energy and nonrigid mechanics of motion are combined to model soft tissue deformation and its dynamics, both of which are further formulated as the dynamics of cellular neural networks to achieve real-time computational performance. The proposed methodology is implemented with a haptic device for interactive soft tissue deformation with force feedback. Experimental results demonstrate that the proposed methodology exhibits nonlinear force-displacement relationship for nonlinear soft tissue deformation. Homogeneous, anisotropic and heterogeneous soft tissue material properties can be modelled through the inherent physical properties of mass points.},
	keywords = {CELLULAR NEURAL NETWORKS; Soft tissue deformation; Reaction-diffusion mechanics; Real-time performance; Haptic feedback},
	year = {2018},
	eissn = {1741-0444},
	pages = {2163-2176},
	orcid-numbers = {Zhang, Jinao/0000-0002-1994-8374}
}

@article{MTMT:26889850,
	title = {Cellular neural network modelling of soft tissue dynamics for surgical simulation},
	url = {https://m2.mtmt.hu/api/publication/26889850},
	author = {Zhang, Jinao and Zhong, Yongmin and Smith, Julian and Gu, Chengfan},
	doi = {10.3233/THC-171337},
	journal-iso = {TECHNOL HEALTH CARE},
	journal = {TECHNOLOGY AND HEALTH CARE},
	volume = {25},
	unique-id = {26889850},
	issn = {0928-7329},
	year = {2017},
	eissn = {1878-7401},
	pages = {S337-S344},
	orcid-numbers = {Zhang, Jinao/0000-0002-1994-8374}
}

@article{MTMT:25312182,
	title = {A CNN-based approach for a class of non-standard hyperbolic partial differential equations modeling distributed parameters (nonlinear) control systems},
	url = {https://m2.mtmt.hu/api/publication/25312182},
	author = {Danciu, Daniela},
	doi = {10.1016/j.neucom.2014.12.092},
	journal-iso = {NEUROCOMPUTING},
	journal = {NEUROCOMPUTING},
	volume = {164},
	unique-id = {25312182},
	issn = {0925-2312},
	year = {2015},
	eissn = {1872-8286},
	pages = {56-70},
	orcid-numbers = {Danciu, Daniela/0000-0002-3854-2986}
}

@article{MTMT:23842641,
	title = {A CNN based approach for solving a hyperbolic PDE arising from a system of conservation laws - The case of the overhead crane},
	url = {https://m2.mtmt.hu/api/publication/23842641},
	author = {Danciu, Daniela},
	doi = {10.1007/978-3-642-38682-4_39},
	journal-iso = {LECT NOTES ARTIF INT},
	journal = {LECTURE NOTES IN ARTIFICIAL INTELLIGENCE},
	volume = {7903 LNCS},
	unique-id = {23842641},
	issn = {0302-9743},
	year = {2013},
	pages = {365-374}
}

@inbook{MTMT:2396597,
	title = {From CNN Dynamics to Cellular Wave Computers},
	url = {https://m2.mtmt.hu/api/publication/2396597},
	author = {Roska, Tamás},
	booktitle = {Chaos, CNN, memristors and beyond},
	doi = {10.1142/9789814434805_0004},
	unique-id = {2396597},
	year = {2013},
	pages = {41-55}
}

@article{MTMT:166292,
	title = {Simulation of 2D inviscid, adiabatic, compressible flows on emulated digital CNN-UM.},
	url = {https://m2.mtmt.hu/api/publication/166292},
	author = {Kocsárdi, S and Nagy, Zoltán and Csík, Árpád and Szolgay, Péter},
	doi = {10.1002/cta.565},
	journal-iso = {INT J CIRC THEOR APP},
	journal = {INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS},
	volume = {37},
	unique-id = {166292},
	issn = {0098-9886},
	year = {2009},
	eissn = {1097-007X},
	pages = {569-585},
	orcid-numbers = {Nagy, Zoltán/0000-0002-0992-7123}
}

@article{MTMT:166293,
	title = {Simulation of two-dimensional supersonic flows on emulated digital CNN-UM.},
	url = {https://m2.mtmt.hu/api/publication/166293},
	author = {Kocsárdi, S and Nagy, Zoltán and Csík, Árpád and Szolgay, Péter},
	doi = {10.1155/2009/923404},
	journal-iso = {EURASIP J ADV SIG PR},
	journal = {EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING},
	volume = {2009},
	unique-id = {166293},
	issn = {1687-6172},
	year = {2009},
	eissn = {1687-6180},
	pages = {1-11},
	orcid-numbers = {Nagy, Zoltán/0000-0002-0992-7123}
}

@inproceedings{MTMT:165383,
	title = {Emulated digital CNN solution for two dimensional compressible flows},
	url = {https://m2.mtmt.hu/api/publication/165383},
	author = {Kocsárdi, S and Nagy, Zoltán and Szolgay, Péter},
	booktitle = {European Conference on Circuit Theory and Design 2007, ECCTD 2007},
	doi = {10.1109/ECCTD.2007.4529593},
	unique-id = {165383},
	year = {2008},
	pages = {288-291},
	orcid-numbers = {Nagy, Zoltán/0000-0002-0992-7123}
}

@inproceedings{MTMT:165921,
	title = {Two-dimensional Compressible Flow Simulation on Emulated Digital CNN-UM},
	url = {https://m2.mtmt.hu/api/publication/165921},
	author = {Kocsárdi, S and Nagy, Zoltán and Csík, Árpád and Szolgay, Péter},
	booktitle = {2008 11th international workshop on cellular neural networks and their applications},
	doi = {10.1109/CNNA.2008.4588672},
	unique-id = {165921},
	year = {2008},
	pages = {169-174},
	orcid-numbers = {Nagy, Zoltán/0000-0002-0992-7123}
}

@inproceedings{MTMT:165352,
	title = {CNN model on cell multiprocessor array},
	url = {https://m2.mtmt.hu/api/publication/165352},
	author = {Nagy, Zoltán and Kék, László and Kincses, Zoltán and Szolgay, Péter},
	booktitle = {European Conference on Circuit Theory and Design 2007, ECCTD 2007},
	doi = {10.1109/ECCTD.2007.4529590},
	unique-id = {165352},
	year = {2008},
	pages = {276-279},
	orcid-numbers = {Nagy, Zoltán/0000-0002-0992-7123; Kincses, Zoltán/0000-0002-7130-9510}
}

@inproceedings{MTMT:165873,
	title = {Toward exploitation of cell multi-processor array in time-consuming applications by using CNN model},
	url = {https://m2.mtmt.hu/api/publication/165873},
	author = {Nagy, Zoltán and Kék, László and Kincses, Zoltán and Kiss, András and Szolgay, Péter},
	booktitle = {2008 11th international workshop on cellular neural networks and their applications},
	doi = {10.1109/CNNA.2008.4588670},
	unique-id = {165873},
	year = {2008},
	pages = {157-162},
	orcid-numbers = {Nagy, Zoltán/0000-0002-0992-7123; Kincses, Zoltán/0000-0002-7130-9510}
}

@article{MTMT:165869,
	title = {Toward exploitation of cell multi-processor array in time-consuming applications by using CNN model},
	url = {https://m2.mtmt.hu/api/publication/165869},
	author = {Nagy, Zoltán and Kék, László and Kincses, Zoltán and Kiss, András and Szolgay, Péter},
	doi = {10.1002/cta.508},
	journal-iso = {INT J CIRC THEOR APP},
	journal = {INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS},
	volume = {36},
	unique-id = {165869},
	issn = {0098-9886},
	year = {2008},
	eissn = {1097-007X},
	pages = {605-622},
	orcid-numbers = {Nagy, Zoltán/0000-0002-0992-7123; Kincses, Zoltán/0000-0002-7130-9510}
}

@inproceedings{MTMT:165318,
	title = {CNN-UM based transversely isotropic elastic wave propagation simulation},
	url = {https://m2.mtmt.hu/api/publication/165318},
	author = {Sonkoly, P and Noé, I and Carcione, J and Nagy, Zoltán and Szolgay, Péter},
	booktitle = {European Conference on Circuit Theory and Design 2007, ECCTD 2007},
	doi = {10.1109/ECCTD.2007.4529592},
	unique-id = {165318},
	year = {2008},
	pages = {284-287},
	orcid-numbers = {Nagy, Zoltán/0000-0002-0992-7123}
}

@inproceedings{MTMT:2014321,
	title = {Emulated digital CNN-UM on different kind of array processors},
	url = {https://m2.mtmt.hu/api/publication/2014321},
	author = {Szolgay, Péter},
	booktitle = {2008 11th international workshop on cellular neural networks and their applications},
	doi = {10.1109/CNNA.2008.4588669},
	unique-id = {2014321},
	year = {2008},
	pages = {154-156}
}

@inproceedings{MTMT:164906,
	title = {FPGA based implementation of water reinjection in geothermal structure},
	url = {https://m2.mtmt.hu/api/publication/164906},
	author = {Kocsárdi, S and Nagy, Zoltán and Kostianev, S and Szolgay, Péter},
	booktitle = {Proceedings of the 2006 10th IEEE International Workshop on Cellular Neural Networks and Their Applications},
	doi = {10.1109/CNNA.2006.341653},
	unique-id = {164906},
	keywords = {Partial differential equations; Water heating; Field programmable gate arrays; CELLULAR NEURAL NETWORKS},
	year = {2006},
	pages = {323-327},
	orcid-numbers = {Nagy, Zoltán/0000-0002-0992-7123}
}

@article{MTMT:165040,
	title = {Seismic wave propagation modelling on emulated digital CNN-UM architecture},
	url = {https://m2.mtmt.hu/api/publication/165040},
	author = {Kozma, P and Nagy, Zoltán and Szolgay, Péter},
	journal-iso = {PERIOD POLYTECH ELECTR ENG},
	journal = {PERIODICA POLYTECHNICA-ELECTRICAL ENGINEERING},
	volume = {49},
	unique-id = {165040},
	issn = {0324-6000},
	year = {2006},
	eissn = {1587-3781},
	pages = {183-193},
	orcid-numbers = {Nagy, Zoltán/0000-0002-0992-7123}
}

@inproceedings{MTMT:164454,
	title = {Elastic wave propagation modeling on emulated digital CNN-UM architecture},
	url = {https://m2.mtmt.hu/api/publication/164454},
	author = {Kozma, P and Sonkoly, P and Szolgay, Péter},
	booktitle = {Cellular neural networks and their applications: Proceedings of the 9th IEEE international workshop, CNNA 2005},
	doi = {10.1109/CNNA.2005.1543177},
	unique-id = {164454},
	year = {2005},
	pages = {126-129}
}

@inproceedings{MTMT:164387,
	title = {Inverse elastic wave propagation modeling on CNN-UM architecture},
	url = {https://m2.mtmt.hu/api/publication/164387},
	author = {Sonkoly, P and Kocsárdi, S and Kozma, P and Szolgay, Péter},
	booktitle = {Proceedings of the 2005 European Conference on Circuit Theory and Design, Vol 1-3},
	unique-id = {164387},
	abstract = {Exploration seismology deals with the use of. generated elastic waves to locate mineral deposits artificially (including hydrocarbons, ores, water, geothermal reservoirs, etc.) archeological sites and to obtain geological information for engineering. The elastic waves generated by an explosion propagate through the examined geological area and recorded on the surface. The structure of the area can be determined by using the recorded data called seismogram. The propagation of elastic waves in an elastic medium can be described by second order partial differential equations. The solution of these kinds of equations requires enormous computation power. In this paper a solution of inverse seismic wave propagation will be presented on Falcon emulated digital CNN-UNI architecture.},
	year = {2005},
	pages = {79-82}
}

@article{MTMT:22618098,
	title = {Emulated digital CNN-UM implementation of a barotropic ocean model},
	url = {https://m2.mtmt.hu/api/publication/22618098},
	author = {Nagy, Z and Szolgay, P},
	doi = {10.1109/IJCNN.2004.1381176},
	journal-iso = {IEEE INT JOINT CONF NEURAL NETWORKS},
	journal = {IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS},
	volume = {4},
	unique-id = {22618098},
	issn = {1098-7576},
	year = {2004},
	pages = {3137-3142}
}

@inproceedings{MTMT:163978,
	title = {Emulated digital CNN-UM implementation of a barotropic ocean model},
	url = {https://m2.mtmt.hu/api/publication/163978},
	author = {Nagy, Zoltán and Szolgay, Péter},
	booktitle = {2004 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-4,PROCEEDINGS},
	doi = {10.1109/IJCNN.2004.1381176},
	unique-id = {163978},
	year = {2004},
	pages = {3137-3142},
	orcid-numbers = {Nagy, Zoltán/0000-0002-0992-7123}
}

@inproceedings{MTMT:22618100,
	title = {Application of cellular neural networks in stress analysis of prismatic bars subjected to torsion},
	url = {https://m2.mtmt.hu/api/publication/22618100},
	author = {Krstic, I and Reljin, B and Kostic, P and Kandic, D},
	booktitle = {2002 6TH SEMINAR ON NEURAL NETWORK APPLICATIONS IN ELECTRICAL ENGINEERING, PROCEEDINGS},
	publisher = {Institute of Electrical and Electronics Engineers},
	unique-id = {22618100},
	year = {2002},
	pages = {129-134}
}

@article{MTMT:163242,
	title = {Toward visual microprocessors. Invited paper},
	url = {https://m2.mtmt.hu/api/publication/163242},
	author = {Roska, Tamás and Rodríguez-Vázquez, Á},
	doi = {10.1109/JPROC.2002.801453},
	journal-iso = {P IEEE},
	journal = {PROCEEDINGS OF THE IEEE},
	volume = {90},
	unique-id = {163242},
	issn = {0018-9219},
	year = {2002},
	eissn = {1558-2256},
	pages = {1244-1257}
}

@inproceedings{MTMT:22618099,
	title = {Character recognition using a cellular neural network},
	url = {https://m2.mtmt.hu/api/publication/22618099},
	author = {Stanic, N and Potrebic, M and Durdevic, D and Dujkovic, D and Kostic, P},
	booktitle = {2002 6TH SEMINAR ON NEURAL NETWORK APPLICATIONS IN ELECTRICAL ENGINEERING, PROCEEDINGS},
	publisher = {Institute of Electrical and Electronics Engineers},
	unique-id = {22618099},
	year = {2002},
	pages = {135-138}
}

@article{MTMT:24072520,
	title = {Stability of 1-D-CNN's with Dirichlet boundary conditions and global propagation dynamics},
	url = {https://m2.mtmt.hu/api/publication/24072520},
	author = {De Sandre, G},
	doi = {10.1109/81.852930},
	journal-iso = {IEEE T CIRC SYST FUND},
	journal = {IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I - FUNDAMENTAL THEORY AND APPLICATIONS},
	volume = {47},
	unique-id = {24072520},
	issn = {1057-7122},
	year = {2000},
	pages = {785-792}
}

@{MTMT:10274025,
	title = {A 20x22 CNN-UM chip with on-chip optical sensors},
	url = {https://m2.mtmt.hu/api/publication/10274025},
	author = {Dominguez-Castro, R and Espejo, S and Rodriguez-Vazquez, A and Carmona, R},
	booktitle = {Towards the Visual Microprocessor: VLSI Design and the Use of Cellular Neural Network Universal Machines},
	publisher = {Wiley},
	unique-id = {10274025},
	year = {2000},
	pages = {213-237}
}

@inproceedings{MTMT:22618101,
	title = {Cellular neural network simulator derived in Delphi},
	url = {https://m2.mtmt.hu/api/publication/22618101},
	author = {Stanic, N and Kostic, P and Reljin, B},
	booktitle = {NEUREL 2000: PROCEEDINGS OF THE 5TH SEMINAR ON NEURAL NETWORK APPLICATIONS IN ELECTRICAL ENGINEERING},
	publisher = {Institute of Electrical and Electronics Engineers},
	unique-id = {22618101},
	year = {2000},
	pages = {125-129}
}

@inproceedings{MTMT:162294,
	title = {A comparison of the different CNN implementations in solving the problem of spatiotemporal dynamics in mechanical systems},
	url = {https://m2.mtmt.hu/api/publication/162294},
	author = {Szolgay, Péter and Hidvégi, Timót and Szolgay, Z and Kozma, P},
	booktitle = {Proceedings of the 2000 6th IEEE International Workshop on Cellular Neural Network and their Applications (CNNA 2000)},
	doi = {10.1109/CNNA.2000.876811},
	unique-id = {162294},
	year = {2000},
	pages = {9-14}
}

@article{MTMT:162103,
	title = {Computer-sensors: spatial-temporal computers for analog array signals, dynamically integrated with sensors},
	url = {https://m2.mtmt.hu/api/publication/162103},
	author = {Roska, Tamás},
	doi = {10.1023/A:1008132715897},
	journal-iso = {J VLSI SIG PROC SYST},
	journal = {JOURNAL OF VLSI SIGNAL PROCESSING: SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY},
	volume = {23},
	unique-id = {162103},
	issn = {0922-5773},
	year = {1999},
	eissn = {1573-109X},
	pages = {221-237}
}

@article{MTMT:22618103,
	title = {Feedback neural network for pattern recognition},
	url = {https://m2.mtmt.hu/api/publication/22618103},
	author = {Salih, I and Smith, SH},
	doi = {10.1117/12.341120},
	journal-iso = {PROCEEDINGS OF SPIE},
	journal = {PROCEEDINGS OF SPIE - THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING},
	volume = {3647},
	unique-id = {22618103},
	issn = {0277-786X},
	year = {1999},
	eissn = {1996-756X},
	pages = {194-201}
}

@article{MTMT:161657,
	title = {CNN-based difference-controlled adaptive non-linear image filters},
	url = {https://m2.mtmt.hu/api/publication/161657},
	author = {Rekeczky, Csaba and Roska, Tamás and Ushida, A},
	doi = {10.1002/(SICI)1097-007X(199807/08)26:4<375::AID-CTA19>3.0.CO;2-#},
	journal-iso = {INT J CIRC THEOR APP},
	journal = {INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS},
	volume = {26},
	unique-id = {161657},
	issn = {0098-9886},
	year = {1998},
	eissn = {1097-007X},
	pages = {375-423}
}

@article{MTMT:10274528,
	title = {Implications of chaos theory for engineering science},
	url = {https://m2.mtmt.hu/api/publication/10274528},
	author = {Baker, G and McRobie, FA and Thompson, JMT},
	doi = {10.1243/0954406971522105},
	journal-iso = {P I MECH ENG C-J MEC},
	journal = {PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE},
	volume = {211},
	unique-id = {10274528},
	issn = {0954-4062},
	year = {1997},
	eissn = {2041-2983},
	pages = {349-363}
}

@article{MTMT:10273544,
	title = {Mapping of one-dimensional Josephson junction arrays onto cellular neural networks and their dynamics},
	url = {https://m2.mtmt.hu/api/publication/10273544},
	author = {Finger, L and Tavsanoglu, V},
	doi = {10.1109/81.572340},
	journal-iso = {IEEE T CIRC SYST FUND},
	journal = {IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I - FUNDAMENTAL THEORY AND APPLICATIONS},
	volume = {44},
	unique-id = {10273544},
	issn = {1057-7122},
	year = {1997},
	pages = {438-445}
}

@article{MTMT:10273547,
	title = {A spectral approach to the study of propagation phenomena in CNNs},
	url = {https://m2.mtmt.hu/api/publication/10273547},
	author = {Civalleri, PP and Gilli, M},
	doi = {10.1002/(SICI)1097-007X(199601/02)24:1<37::AID-CTA902>3.0.CO;2-S},
	journal-iso = {INT J CIRC THEOR APP},
	journal = {INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS},
	volume = {24},
	unique-id = {10273547},
	issn = {0098-9886},
	year = {1996},
	eissn = {1097-007X},
	pages = {37-47}
}

@inproceedings{MTMT:160818,
	title = {Adaptive histogram equalization with Cellular Neural Networks},
	url = {https://m2.mtmt.hu/api/publication/160818},
	author = {Csapodi, Márton and Roska, Tamás},
	booktitle = {Fourth IEEE International Workshop on Cellular Neural Networks and their Applications, CNNA-96: Proceedings},
	unique-id = {160818},
	year = {1996},
	pages = {81-86}
}

@article{MTMT:10273545,
	title = {Cellular neural networks as a general massively parallel computational paradigm},
	url = {https://m2.mtmt.hu/api/publication/10273545},
	author = {Destri, G and Marenzoni, P},
	doi = {10.1002/(SICI)1097-007X(199605/06)24:3<397::AID-CTA924>3.0.CO;2-N},
	journal-iso = {INT J CIRC THEOR APP},
	journal = {INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS},
	volume = {24},
	unique-id = {10273545},
	issn = {0098-9886},
	year = {1996},
	eissn = {1097-007X},
	pages = {397-407}
}

@{MTMT:20278394,
	title = {Mapping of one-dimensional josephson junction arrays onto cellular neural networks},
	url = {https://m2.mtmt.hu/api/publication/20278394},
	author = {Finger, L and Tavsanoglu, V},
	booktitle = {Fourth IEEE International Workshop on Cellular Neural Networks and their Applications, CNNA-96: Proceedings},
	unique-id = {20278394},
	year = {1996},
	pages = {345-350}
}

@article{MTMT:10274344,
	title = {Design and learning with cellular neural networks},
	url = {https://m2.mtmt.hu/api/publication/10274344},
	author = {Nossek, JA},
	doi = {10.1002/(SICI)1097-007X(199601/02)24:1<15::AID-CTA900>3.0.CO;2-5},
	journal-iso = {INT J CIRC THEOR APP},
	journal = {INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS},
	volume = {24},
	unique-id = {10274344},
	issn = {0098-9886},
	year = {1996},
	eissn = {1097-007X},
	pages = {15-24}
}

@inproceedings{MTMT:160738,
	title = {Distance preserving 1D turing-wave models via CNN, implementation of complex-valued CNN and solving a simple inverse pattern problem (detection)},
	url = {https://m2.mtmt.hu/api/publication/160738},
	author = {Tóth, Gábor András and Földesy, Péter and Roska, Tamás},
	booktitle = {Fourth IEEE International Workshop on Cellular Neural Networks and their Applications, CNNA-96: Proceedings},
	doi = {10.1109/CNNA.1996.566503},
	unique-id = {160738},
	year = {1996},
	pages = {109-114},
	orcid-numbers = {Földesy, Péter/0000-0001-7495-0971}
}

@article{MTMT:10273539,
	title = {VLSI implementation of locally connected neural network for solving partial differential equations},
	url = {https://m2.mtmt.hu/api/publication/10273539},
	author = {Yentis, R and Zaghloul, ME},
	doi = {10.1109/81.526685},
	journal-iso = {IEEE T CIRC SYST FUND},
	journal = {IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I - FUNDAMENTAL THEORY AND APPLICATIONS},
	volume = {43},
	unique-id = {10273539},
	issn = {1057-7122},
	year = {1996},
	pages = {687-690}
}

@article{MTMT:160581,
	title = {Simulating nonlinear waves and partial differential equations via CNN. Part 2. Typical examples},
	url = {https://m2.mtmt.hu/api/publication/160581},
	author = {Kozek, Tibor and Chua, LO and Roska, Tamás and Wolf, D and Tetzlaff, R and Puffer, F},
	doi = {10.1109/81.473591},
	journal-iso = {IEEE T CIRC SYST FUND},
	journal = {IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I - FUNDAMENTAL THEORY AND APPLICATIONS},
	volume = {42},
	unique-id = {160581},
	issn = {1057-7122},
	year = {1995},
	pages = {816-820}
}

@article{MTMT:160568,
	title = {Simulating nonlinear waves and partial differential equations via CNN. Part 1. Basic techniques},
	url = {https://m2.mtmt.hu/api/publication/160568},
	author = {Roska, Tamás and Chua, LO and Wolf, D and Kozek, Tibor and Tetzlaff, R and Puffer, F},
	doi = {10.1109/81.473590},
	journal-iso = {IEEE T CIRC SYST FUND},
	journal = {IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I - FUNDAMENTAL THEORY AND APPLICATIONS},
	volume = {42},
	unique-id = {160568},
	issn = {1057-7122},
	year = {1995},
	pages = {807-815}
}

@article{MTMT:160557,
	title = {Analogic CNN algorithms for some image compression and restoration tasks},
	url = {https://m2.mtmt.hu/api/publication/160557},
	author = {Venetianer, Péter László and Werblin, F and Roska, Tamás and Chua, LO},
	doi = {10.1109/81.386161},
	journal-iso = {IEEE T CIRC SYST FUND},
	journal = {IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I - FUNDAMENTAL THEORY AND APPLICATIONS},
	volume = {42},
	unique-id = {160557},
	issn = {1057-7122},
	year = {1995},
	pages = {278-284}
}

@CONFERENCE{MTMT:10273535,
	title = {Some problems of molecular physics solved by CNN},
	url = {https://m2.mtmt.hu/api/publication/10273535},
	author = {Jankowski, S and Mazur, C and Wanczuk, R},
	booktitle = {Nonlinear theory and its applications: Proceedings of the International symposium, NOLTA '93},
	unique-id = {10273535},
	year = {1994},
	pages = {17-22}
}

@article{MTMT:10273534,
	title = {Mapping nonlinear Lattice Equations onto cellular neural networks},
	url = {https://m2.mtmt.hu/api/publication/10273534},
	author = {Paul, S and Huper, K and Nossek, JA and Chua, LO},
	doi = {10.1109/81.222800},
	journal-iso = {IEEE T CIRC SYST FUND},
	journal = {IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I - FUNDAMENTAL THEORY AND APPLICATIONS},
	volume = {40},
	unique-id = {10273534},
	issn = {1057-7122},
	year = {1993},
	pages = {196-203}
}