05509nam 2201573z- 450 991055769930332120231214133051.0(CKB)5400000000044564(oapen)https://directory.doabooks.org/handle/20.500.12854/76727(EXLCZ)99540000000004456420202201d2021 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierModelling and Control of Mechatronic and Robotic SystemsBasel, SwitzerlandMDPI - Multidisciplinary Digital Publishing Institute20211 electronic resource (404 p.)3-0365-1122-9 3-0365-1123-7 Currently, the modelling and control of mechatronic and robotic systems is an open and challenging field of investigation in both industry and academia. The book encompasses the kinematic and dynamic modelling, analysis, design, and control of mechatronic and robotic systems, with the scope of improving their performance, as well as simulating and testing novel devices and control architectures. A broad range of disciplines and topics are included, such as robotic manipulation, mobile systems, cable-driven robots, wearable and rehabilitation devices, variable stiffness safety-oriented mechanisms, optimization of robot performance, and energy-saving systems.Technology: general issuesbicsscbionic mechanism designsynthesisexoskeletonfinger motion rehabilitationsuper-twisting control lawrobot manipulatorsfast terminal sliding mode controlsemi-active seat suspensionintegrated modelcontrolfuzzy logic-based self-tuningPIDsuper-twistingsliding mode extended state observersaturation functionfuzzy logicattenuate disturbancepHRIvariable stiffness actuatorV2SOMfriendly cobotssafety criteriahuman-robot collisionsunderwater vehicle-manipulator systemmotion planningcoordinated motion controlinertial delay controlfuzzy compensatorextended Kalman filterfeedback linearizationCPGself-growing networkquadruped robottrot gaitdirectional indexserial robotperformance evaluationkinematicshydraulic pressenergy savingenergy efficiencyinstalled powerprocessing performancespace roboticsplanetary surface explorationterrain awarenessmechanics of vehicle-terrain interactionvehicle dynamicsmulti-support shaft system vibration controlcombined simulationtransverse bending vibrationSmart Springadaptive controlhydraulicsdifferential cylinderfeedforwardmotion controlmanipulator armtrajectory optimization"whip-lashing" methodreduction of cycle timetrajectory planningSolidWorks and MATLAB software applicationsdynamic modelingmultibody simulationrobotic landervariable radius drumimpact analysiscable-driven parallel robotscable-suspended robotsdynamic workspacethrowing robotscasting robotredesignslider-crank mechanismoptimizationsynthesis problemrehabilitation devicessix-wheel drive (6WD)skid steeringelectric unmanned ground vehicle (EUGV)driving force distributionvehicle motion controlmaneuverability and stabilityhexapod robotpath planningenergy consumptioncost of transportheuristic optimizationmobile robotstractor-trailerwheel slip compensationgait optimizationgenetic algorithmquadrupedal locomotionevolutionary programmingoptimal contact forcesmicro aerial vehiclesvisual-based controlKalman filterTechnology: general issuesGasparetto Alessandroedt97528Seriani StefanoedtScalera LorenzoedtGasparetto AlessandroothSeriani StefanoothScalera LorenzoothBOOK9910557699303321Modelling and Control of Mechatronic and Robotic Systems3022621UNINA03980nam 2201009z- 450 991034685660332120231214133353.03-03897-665-2(CKB)4920000000095101(oapen)https://directory.doabooks.org/handle/20.500.12854/50225(EXLCZ)99492000000009510120202102d2019 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierInformation Theory in NeuroscienceMDPI - Multidisciplinary Digital Publishing Institute20191 electronic resource (280 p.)3-03897-664-4 As the ultimate information processing device, the brain naturally lends itself to being studied with information theory. The application of information theory to neuroscience has spurred the development of principled theories of brain function, and has led to advances in the study of consciousness, as well as to the development of analytical techniques to crack the neural code—that is, to unveil the language used by neurons to encode and process information. In particular, advances in experimental techniques enabling the precise recording and manipulation of neural activity on a large scale now enable for the first time the precise formulation and the quantitative testing of hypotheses about how the brain encodes and transmits the information used for specific functions across areas. This Special Issue presents twelve original contributions on novel approaches in neuroscience using information theory, and on the development of new information theoretic results inspired by problems in neuroscience.synergyGibbs measurescategorical perceptionentorhinal cortexneural networkperceived similaritygraph theoretical analysisordernessnavigationnetwork eigen-entropyIsing modelhigher-order correlationsdiscriminationinformation theoryrecursiongoodnessconsciousnessneurosciencefeedforward networksspike train statisticsdecodingeigenvector centralitydiscrete Markov chainssubmodularityfree-energy principleinfomax principleneural information propagationintegrated informationmismatched decodingmaximum entropy principleperceptual magnetgraph theoryinternal model hypothesischannel capacitycomplex networksrepresentationlatchingnoise correlationsindependent component analysismutual information decompositionconnectomeredundancymutual informationinformation entropy productionunconscious inferencehippocampusneural population codingspike-time precisionneural codingmaximum entropyneural codePotts modelpulse-gatingfunctional connectomeintegrated information theoryminimum information partitionbrain networkQueyranne’s algorithmprincipal component analysisPiasini Eugenioauth1292375Panzeri StefanoauthBOOK9910346856603321Information Theory in Neuroscience3022229UNINA