msp430The LDC1312 and LDC1314 are 2- and 4-channel,
1? Easy-to-use – minimal configuration required
12-bit inductance to digital converters (LDCs) for
? Measure up to 4 sensors with one IC
inductive sensing solutions. With multiple channels ? Multiple channels support environmental and and support for remote sensing, the LDC1312 and aging compensation LDC1314 enable the performance and reliability benefits of inductive sensing to be realized at minimal? Multi-channel remote sensing provides lowest cost and power. The products are easy to use, onlysystem cost requiring that the sensor frequency be within 1 kHz ? Pin-compatible medium and high-resolution and 10 MHz to begin sensing. The wide 1 kHz to 10 options MHz sensor frequency range also enables use of very small PCB coils, further reducing sensing– LDC1312/4: 2/4-ch 12-bit LDC solution cost and size.– LDC1612/4: 2/4-ch 28
The CommScope InstaPATCH? 360 and ReadyPATCH? solutions utilize a
standards-compliant multi-fiber connector to provide high density termination
capability. The connector is called an MPO (Multi-fiber Push On) connector by
the standards. In many cases, multi-fiber connector products are referred to as
MTP connectors. This document is intended to clarify the difference between the two terms – MPO and MTP.
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Reconstruction- and example-based super-resolution
(SR) methods are promising for restoring a high-resolution
(HR) image from low-resolution (LR) image(s). Under large
magnification, reconstruction-based methods usually fail
to hallucinate visual details while example-based methods
sometimes introduce unexpected details. Given a generic
LR image, to reconstruct a photo-realistic SR image and
to suppress artifacts in the reconstructed SR image, we
introduce a multi-scale dictionary to a novel SR method
that simultaneously integrates local and non-local priors.
The local prior suppresses artifacts by using steering kernel regression to predict the target pixel from a small local
area. The non-local prior enriches visual details by taking
a weighted average of a large neighborhood as an estimate
of the target pixel. Essentially, these two priors are complementary to each other. Experimental results demonstrate
that the proposed method can produce high quality SR recovery both quantitatively and perceptually.
New applications such as video conferencing, video on demand, multi-
media transcoders, Voice-over-IP (VoIP), intrusion detection, distributed
collaboration, and intranet security require advanced functionality from
networks beyond simple forwarding congestion control techniques.
Emerging technologies such as WiFi and WiMAX are profoundly changing the
landscape of wireless broadband. As we evolve into future generation wireless
networks, a primary challenge is the support of high data rate, integrated multi-
media type traffic over a unified platform. Due to its inherent advantages in
high-speed communication, orthogonal frequency division multiplexing (OFDM)
has become the modem of choice for a number of high profile wireless systems
(e.g., DVB-T, WiFi, WiMAX, Ultra-wideband).
Employing multiple transmit and receive antennas, namely using multi-input multi-output
(MIMO) systems, has proven to be a major breakthrough in providing reliable wireless
communication links. Since their invention in the mid-1990s, transmit diversity, achieved
through space-time coding, and spatial multiplexing schemes have been the focus of much
research in the area of wireless communications.
Today’s wireless services have come a long way since the roll out of the
conventional voice-centric cellular systems. The demand for wireless access
in voice and high rate data multi-media applications has been increasing.
New generation wireless communication systems are aimed at accommodating
this demand through better resource management and improved transmission
technologies.
