Read e-book online Computer Vision PDF

By Linda G. Shapiro

ISBN-10: 0130307963

ISBN-13: 9780130307965

(Pearson schooling) A textbook and reference for college students and practitioners, proposing the required idea for paintings in fields the place major details needs to be extracted from photos. issues lined contain databases and digital and augmented truth, and the textual content comprises greater than 250 routines and programming tasks. DLC: desktop imaginative and prescient.

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6. The International 10-20 System of Electrodes Placement. , 2010] The next stage is extracting the underlying information in the signal. Depending on the purpose of the study, this stage can be feature extraction or event detection as shown in Figure 7. If the EEG signal is to be used for activating equipment, a simple and an easy way is to detect an event from the signal, for example eye blinks and use the output which in the form of pulses to activate the equipment. Classification process is necessary if specific features are needed to perform the activation.

51075112, and the Royal Society of UK under Grant No. 16558. 8. G. G. of sprung mass and the roll center; Ip: equivalent moment of inertia of multiple parts reflected to the pinion axis. The multiple parts include the motor, the gear assist mechanism, and the pinion; Iw: wheel moment of inertia about its spin axis; Ix, Iy, Iz: roll moment of inertia, pitch moment of inertia, and yaw moment of inertia of sprung mass; Ixz: product of inertia of sprung mass about the roll and yaw axes; J: performance index; kaf, kar: stiffness of the anti-roll bars for the front, rear suspension; ke, kde: scaling factor; ks : torsional stiffness of the torque sensor; ksi: stiffness of the suspension at wheel i; kti: stiffness of tyre at wheel i; 28 Advances in Mechatronics k : cornering stiffness of the tyre; K: state feedback gain matrix; L: wheel base; m, ms, mui : mass of the vehicle, sprung mass, and unsprung mass at wheel i; MASS, MESP: distributed torques for the ASS and the ESP, respectively; Md, Mp: braking/traction torque and pitch torque; MZC: corrective yaw moment generated by the ESP controller; n1, n2: weighting coefficient; N: weighting matrix; N2: speed reduction ratio of the rack-pinion mechanism; pw : pressure of the brake wheel cylinder; q1,…, q11, r1,…, r4: weighting coefficient; Q, R: weighting matrix; Rb: brake radius; Rw: tyre rolling radius; S: vehicle stability factor; T0: ideal steering torque applied on the steering wheel; Tc: torque applied on the steering wheel; Ti: wheel torque at wheel i; Tm: assist torque applied on the steering column; Tr: aligning torque transferred from tyres to the pinion; Tzwi: aligning torque acting on the tyre i; U, U1, U2: control input vector, control force vector, and road excitation vector, respectively;.

Block diagram of the adaptive fuzzy logic controller for ESP. As shown in Fig. 10, the AFL controller consists of a FLC and an adaptive mechanism. To design the AFL controller, the yaw rate and the sideslip angle of the vehicle are selected as the control objectives. The yaw rate can be measured by a gyroscope, but the sideslip angle cannot be directly measured and thus has to be estimated by an observer. 4. The linearized state space equation of the 2-DOF vehicle model is derived as follows, with the assumptions of a constant forward speed and a small sideslip angle.

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Computer Vision by Linda G. Shapiro

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