sba, a C/C++ package for generic sparse bundle adjustment is almost invariably used as the last step of every feature-based multiple view reconstruction vision algorithm to obtain optimal 3D structure and motion (i.e. camera matrix) parameter estimates. Provided with initial estimates, BA simultaneously refines motion and structure by minimizing the reprojection error between the observed and predicted image points.
The AP2406 is a 1.5Mhz constant frequency, slope compensated current mode PWM step-down converter. The device integrates a main switch and a synchronous rectifier for high efficiency without an external Schottky diode. It is ideal for powering portable equipment that runs from a single cell lithium-Ion (Li+) battery. The AP2406 can supply 600mA of load current from a 2.5V to 5.5V input voltage. The output voltage can be regulated as low as 0.6V. The AP2406 can also run at 100% duty cycle for low dropout operation, extending battery life in portable system. Idle mode operation at light loads provides very low output ripple voltage for noise sensitive applications.
The AP2406 is offered in a low profile (1mm) 5-pin, thin SOT package, and is available in an adjustable version and fixed output voltage of 1.2V, 1.5V and 1.8V
obot control, a subject aimed at making robots behave as desired, has been
extensively developed for more than two decades. Among many books being
published on this subject, a common feature is to treat a robot as a single
system that is to be controlled by a variety of control algorithms depending on
different scenarios and control objectives. However, when a robot becomes more
complex and its degrees of freedom of motion increase substantially, the needed
control computation can easily go beyond the scope a modern computer can
handle within a pre-specified sampling period. A solution is to base the control
on subsystem dynamics.
A decade ago, I first wrote that people moved, and networks needed to adapt to the
reality that people worked on the go. Of course, in those days, wireless LANs came
with a trade-off. Yes, you could use them while moving, but you had to trade a great
deal of throughput to get the mobility. Although it was possible to get bits anywhere,
even while in motion, those bits came slower. As one of the network engineers I worked
with put it, “We’ve installed switched gigabit Ethernet everywhere on campus, so I
don’t understand why you’d want to go back to what is a 25-megabit hub.” He un-
derestimated the allure of working on the go.
By definition, the term “mobile-radio communications” describes any
radio communication link between two terminals of which one or both
are in motion or halted at unspecified locations and of which one may
actually be a fixed terminal such as a base station. This definition
applies to both mobile-to-mobile and mobile-to-fixed radio communica-
tion links. The mobile-to-mobile link could in fact consist of a mobile-
to-fixed-to-mobile radio communication link.The term “mobile” applies
to land vehicles, ships at sea, aircraft, and communications satellites.
In tactical situations, mobile-radio systems may include any or all of
these types of mobile terminals.
This paper presents a Hidden Markov Model (HMM)-based speech
enhancement method, aiming at reducing non-stationary noise from speech
signals. The system is based on the assumption that the speech and the noise
are additive and uncorrelated. Cepstral features are used to extract statistical
information from both the speech and the noise. A-priori statistical
information is collected from long training sequences into ergodic hidden
Markov models. Given the ergodic models for the speech and the noise, a
compensated speech-noise model is created by means of parallel model
combination, using a log-normal approximation. During the compensation, the
mean of every mixture in the speech and noise model is stored. The stored
means are then used in the enhancement process to create the most likely
speech and noise power spectral distributions using the forward algorithm
combined with mixture probability. The distributions are used to generate a
Wiener filter for every observation. The paper includes a performance
evaluation of the speech enhancer for stationary as well as non-stationary
noise environment.
Control systems are used to regulate an enormous variety of machines, products, and
processes. They control quantities such as motion, temperature, heat flow, fluid flow,
fluid pressure, tension, voltage, and current. Most concepts in control theory are based
on having sensors to measure the quantity under control. In fact, control theory is
often taught assuming the availability of near-perfect feedback signals. Unfortunately,
such an assumption is often invalid. Physical sensors have shortcomings that can
degrade a control system.
