Above are papers related to the following paper: [Paper_ID] Paper #1105622. 	[Title] Stability and Chaos in an Inertial Two Neuron System  in Statistical Mechanics and Complex Systems [Abstract] Inertia is added to a continuous-time, Hopfield [1], effective neuron system. We explore the effects on the stability of the fixed points of the system. A two neuron system with one or two inertial terms added is shown to exhibit chaos. The chaos is confirmed by Lyapunov exponents, power spectra, and phase space plots. Key words: chaos, Hopfield model, effective neurons, Lyapunov exponent, inertia. Please summarise all the given information.

Above are papers related to the following paper: [Paper_ID] Paper #430574. 	[Title] Nonlinear Resonance in Neuron Dynamics  in Statistical Mechanics and Complex Systems [Abstract] Hubler's technique using aperiodic forces to drive nonlinear oscillators to resonance is analyzed. The oscillators being examined are effective neurons that model Hopfield neural networks. The method is shown to be valid under several different circumstances. It is verified through analysis of the power spectrum, force, resonance, and energy transfer of the system. Please summarise all the given information.

Paper #1105622 has the title `Stability and Chaos in an Inertial Two Neuron System  in Statistical Mechanics and Complex Systems  
` and the abstract `Inertia is added to a continuous-time, Hopfield [1], effective neuron system. We explore the effects on the stability of the fixed points of the system. A two neuron system with one or two inertial terms added is shown to exhibit chaos. The chaos is confirmed by Lyapunov exponents, power spectra, and phase space plots. Key words: chaos, Hopfield model, effective neurons, Lyapunov exponent, inertia. 
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Question: Which category should Paper #1105622 be classified as ?
You can select one from ['Neural_Networks', 'Case_Based', 'Theory', 'Reinforcement_Learning', 'Probabilistic_Methods', 'Rule_Learning', 'Genetic_Algorithms'].


Paper #1105622 has the title `Stability and Chaos in an Inertial Two Neuron System  in Statistical Mechanics and Complex Systems  
` and the abstract `Inertia is added to a continuous-time, Hopfield [1], effective neuron system. We explore the effects on the stability of the fixed points of the system. A two neuron system with one or two inertial terms added is shown to exhibit chaos. The chaos is confirmed by Lyapunov exponents, power spectra, and phase space plots. Key words: chaos, Hopfield model, effective neurons, Lyapunov exponent, inertia. 
`.
Question: Which category should Paper #1105622 be classified as ?
You can select one from ['Neural_Networks', 'Case_Based', 'Theory', 'Reinforcement_Learning', 'Probabilistic_Methods', 'Rule_Learning', 'Genetic_Algorithms'].

This paper should be classified into: Neural_Networks