This chapter enables the reader to:
• Know the content and organization of this book, and how to use it to analyze
and model radar system performance
• Understand the concept of radar operation, the functions performed by radar,
and how radar may be used in various applications
• Understand the characteristics of Functional radar models and how they are
used to analyze overall radar performance.
Abstract—Stable direct and indirect decentralized adaptive radial basis
neural network controllers are presented for a class of interconnected
nonlinear systems. The feedback and adaptation mechanisms for each
subsystem depend only upon local measurements to provide asymptotic
tracking of a reference trajectory. Due to the Functional approximation
capabilities of radial basis neural networks, the dynamics for each
subsystem are not required to be linear in a set of unknown coeffi cients
as is typically required in decentralized adaptive schemes. In addition,
each subsystem is able to adaptively compensate for disturbances and
interconnections with unknown bounds.
FP + OOP = Haskell. The programming language Haskell adds object-oriented Functionality (using a concept
known as
type classes
) to a pure Functional programming framework. This paper describes
these extensions and analyzes its accomplishments as well as some problems.
The TJA1040 is an advanced high speed CAN transceiver for use in
automotive and general industrial applications. It supports the differential
bus signal representation described in the international standard for
in-vehicle high speed CAN applications (ISO11898). CAN (Controller Area
Network) is the standard protocol for serial in-vehicle bus communication,
particularly for Engine Management and Body Multiplexing.
The TJA1040 provides a Standby mode, as known from its Functional
predecessors PCA82C250 and PCA82C251, but with significantly
reduced power consumption. Besides the excellent low-power behavior
the TJA1040 offers several valuable system improvements. Highlights are
the absolute passive bus behavior if the device is unpowered as well as
the excellent EMC performance.
The TAS3204 is a highly-integrated audio system-on-chip (SOC) consisting of a fully-programmable, 48-bit digital audio processor, a 3:1 stereo analog input MUX, four ADCs, four DACs, and other analog Functionality. The TAS3204 is programmable with the graphical PurePath Studio? suite of DSP code development software. PurePath Studio is a highly intuitive, drag-and-drop environment that minimizes software development effort while allowing the end user to utilize the power and flexibility of the TAS3204’s digital audio processing core.
TAS3204 processing capability includes speaker equalization and crossover, volume/bass/treble control, signal mixing/MUXing/splitting, delay compensation, dynamic range compression, and many other basic audio functions. Audio functions such as matrix decoding, stereo widening, surround sound virtualization and psychoacoustic bass boost are also available with either third-party or TI royalty-free algorithms.
The TAS3204 contains a custom-designed, fully-programmable 135-MHz, 48-bit digital audio processor. A 76-bit accumulator ensures that the high precision necessary for quality digital audio is maintained during arithmetic operations.
Four differential 102 dB DNR ADCs and four differential 105 dB DNR DACs ensure that high quality audio is maintained through the whole signal chain as well as increasing robustness against noise sources such as TDMA interference.
The TAS3204 is composed of eight Functional blocks:
Clocking System
Digital Audio Interface
Analog Audio Interface
Power supply
Clocks, digital PLL
I2C control interface
8051 MCUcontroller
Audio DSP – digital audio processing
特性
Digital Audio Processor
Fully Programmable With the Graphical, Drag-and-Drop PurePath Studio? Software Development Environment
135-MHz Operation
48-Bit Data Path With 76-Bit Accumulator
Hardware Single-Cycle Multiplier (28 × 48)
The family of recent wireless standards included the optional employment of Multiple-Input
Multiple-Output(MIMO)techniques.This was motivatedby the observationaccordingto the
classic Shannon–Hartley law that the achievable channel capacity increases logarithmically
with the transmit power. In contrast, the MIMO capacity increases linearly with the number
of transmit antennas, provided that the number of receive antennas is equal to the number
of transmit antennas. With the further proviso that the total transmit power is increased in
proportion to the number of transmit antennas, a linear capacity increase is achieved upon
increasing the transmit power, which justifies the spectacular success of MIMO systems.
The family of recent wireless standards included the optional employment of MIMO tyechniques.
This was motivated by the observation according to the classic Shannon-Hartley law the achiev-
able channel capacity increases logarithmically with the transmit power. By contrast, the MIMO
capacity increases linearly with the number of transmit antennas, provided that the number of
receive antennas is equal to the number of transmit antennas.
adio Frequency Identification (RFID) is a rapidly developing automatic wireless data-collection
technology with a long history.The first multi-bit Functional passive RFID systems,with a range of
several meters, appeared in the early 1970s, and continued to evolve through the 1980s. Recently,
RFID has experienced a tremendous growth,due to developments in integrated circuits and radios,
and due to increased interest from the retail industrial and government.
MIT App Inventor is an innovative beginner’s introduction to programming and app
creation that transforms the complex language of text-based coding into visual, drag-and-
drop building blocks. The simple graphical interface grants even an inexperienced novice
the ability to create a basic, fully Functional app within an hour or less.
In the early days, embedded systems were built primarily by engineers in a
pretty exclusive club. Embedded devices and software tools were expensive,
and building a Functional prototype required significant software engineering
and electrical engineering experience.
