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NXP BV (Eindhoven, The Netherlands) has said it will demonstrate a microcontroller based on the ARM Cortex-M4 at the Embedded Systems Conference in San Jose, California. NXP was one of the first companies to license the Cortex-M4 processor core and a chip has been implemented using a low-leakage 90-nm process technology. This enables performance in excess of 150-MHz clock frequency, NXP said. NXP has added proprietary power-down techniques to reduce power consumption. The ESC Silicon Valley demo will show that a 7-channel audio graphic equalizer application processing 32-bit precision audio data requires only 12 MHz of CPU bandwidth using the Cortex-M4 DSP extensions, and 60 MIPs without. The core includes DSP extensions not usually found inside a microcontroller and NXP's implementation are aimed at a broad set of applications including motor control, digital power control and embedded audio.

There are severe flaws within the Harmonic-Balance and SPICE programs now widely used. Mentioned as far back as within an abstract of Session WSO at the 2008 IEEE International Microwave Symposium: "Even though nonlinear circuit-analysis software has been in use for many years, users still have difficulty obtaining valid results with existing methods.  Recognized problems include poor accuracy, convergence difficulties, long simulation times, and unstable results (i.e., results that vary greatly with minor changes in parameters).  These problems are encountered in both harmonic-balance and time-domain simulations."

In earlier articles on intelligent sensor design, we saw how valuable they can be to both end users and those who manufacture and sell them. It’s now time to delve more deeply into what it takes to make intelligent sensors work.   The first step in that journey is to develop a solid, intuitive understanding of the principles of digital signal processing(DSP). Unlike many introductory DSP articles and texts, the focus here will be on presenting and using the important concepts rather than deriving them, for the simple reason that addressing the subject in depth is a book-sized, not a chapter-sized, project.

Given the maturity of MOSFETs, selecting one for your next design may seem deceptively simple. Engineers are familiar with the figures of merit on a MOSFET data sheet. Selecting a MOSFET requires the engineer to use their expertise in scrutinizing different specifications for individual applications. In an application such as a load switch in a server power supply, the switching aspects of a MOSFET matter little because the MOSFET is on almost 100% of the time. The on resistance (RDS(ON)) may be the key figure of merit in such an application. Still other applications, including switching power supplies, use MOSFETs as active switches, and cause the engineer to value other MOSFET performance parameters. Let us consider some applications and their prioritization of MOSFET specifications.

Recent advances in the size and performance of FPGAs, coupled with advantages in time-to-market, field-reconfigurability and lower up-front costs, make FPGAs ideally suited to a wide range of commercial and defense applications [6]. In addition, FPGAs generality and reconfigurability provide important protections against the introduction of Trojan horses during semiconductor manufacturing process[8]. As a result, FPGA applications increasingly involve highly-sensitive intellectual property and trade-secrets, as well as cryptographic keys and algorithms [7].

In high-end audio equipment, careful selection of resistors is one of the best ways to avoid or minimize noise and distortion in the signal path. This paper describes the noise generation in resistors manufactured using the various available resistor technologies and quantifies the noise insertion typical for each type.

High Level Synthesis Architectural Optimization Basics In part 1 of this article we introduced basic filter bank theory and used the Synplify DSP High Level Synthesis (HLS) tool to implement an example filter bank into three alternative architectures. In part 2 we dive deeper into these three architectures to better understand how these filters work. We will also examine the HLS optimizations we applied and the resulting benefits. Example Filter Bank Review Before we proceed, let's quickly review our filter bank example. Our example, shown in Figure 1, is a size 16 DFT filter bank. The color scheme shows the sample rate change where a 16 MHz input sample rate (red) has been chosen and the output sample rate is downsampled by 16 (green).

Single-walled carbon nanotube (SWCNT)-based thin film transistors (TFTs) could be at the core of next-generation flexible electronics – displays, electronic circuits, sensors, memory chips, and other applications that are transitioning from rigid substrates, such as silicon and glass, to flexible substrates. What's holding back commercial applications is that industrial-type manufacturing of large scale SWCNT-based nanoelectronic devices isn't practical yet because controlling the morphology of single-walled carbon nanotubes is still causing headaches for materials engineers.

This article features an example chapter from a new *Hot-off-the-Press* book on FPGA Design that just recently hit the streets in August 2010. This chapter is reproduced here with the kind permission of the publisher – Springer. This book -- FPGA Design: Best Practices for Team-Based Design -- describes best practices for successful FPGA design. It is the result of the author’s meetings with hundreds of customers on the challenges facing each of their FPGA design teams. By gaining an understanding into their design environments, processes, what works and what does not work, key areas of concern in implementing system designs have been identified and a recommended design methodology to overcome these challenges has been developed.

Ever since graphene was first produced in a lab at the University of Manchester in 2004, researchers around the world have been fascinated with its potential in electronics applications. Graphene possessed all the benefits of carbon nanotubes (CNTs), namely its charged-carrier mobility, but it didn’t have any of the down sides, such as CNTs’ need for different processing techniques than silicon and the intrinsic difficulty of creating interconnects for CNTs. But all was not easy for applying graphene to electronics applications. One of the fundamental problems for graphene was its lack of a band gap, which left it with a very low on-off ratio measured at about 10 as compared to in the 100s for silicon. Now this fundamental hurdle has been overcome. Based on research led by Phaedon Avouris at IBM’s IBM T.J. Watson Research Center, Yorktown Heights, New York, IBM is reporting that they have created a significant band gap in graphene.

Not so long ago, artists routinely made their own paints using all sorts of odd ingredients: clay, linseed oil, ground-up insects—whatever worked. It was a crude and rather ad hoc process, but the results were used to create some of the greatest paintings in the world. Today I and other scientists are developing our own special paints. We’re not trying to compete with Vermeer or Gauguin, though. We hope to create masterpieces of a more technical nature: optoelectronic components that will make for better photovoltaic cells, imaging sensors, and optical communications equipment. And we’re not mixing and matching ingredients quite so haphazardly. Instead, we’re using our blossoming understanding of the world of nanomaterials to design the constituents of our paints at the molecular level.

PC-compatible industrial computers are increasing in computing power at a rapid rate due to the availability of multi-core microprocessor chips, and Microsoft Windows has become the de-facto software platform for implementing human-machine interfaces (HMIs). PCs are also becoming more reliable. With these trends, the practice of building robotic systems as complex multi-architecture, multi-platform systems is being challenged. It is now becoming possible to integrate all the functions of machine control and HMI into a single platform, without sacrificing performance and reliability of processing. Through new developments in software, we are seeing industrial systems evolving to better integrate Windows with real-time functionality such as machine vision and motion control. Software support to simplify motion control algorithm implementation already exists for the Intel processor architecture.

The consumer handheld market is growing by leaps and bounds. With more processing power and increased support for more applications, portable products are cross-pollinating with traditional computing systems even as the product life cycle has decreased considerably in this market segment. As a result, especially in this era of economic slowdown, it is imperative that new products meet the time-to-market window to gain maximum acceptance. A decrease in product life cycles requires a reduced development cycle and an increased emphasis on reusability and reprogrammability. The emerging handheld market is also seeing interesting trends in which each individual device in a family has lower volumes but there is more customization across the series of devices, effectively upping the total unit volumes. The key challenge then becomes how to develop a system that is widely reusable and also customizable. These requirements have led designers increasingly to turn to the FPGA for handheld-product development. The FPGA has become more powerful and feature-rich, while gate counts, area and frequency have increased. FPGA development and turnaround cycles are considerably shorter than those of custom ASICs, and the added advantage of reprogrammability can make the FPGA a more compelling solution for handheld embedded systems.

The first textbook of its kind, Programming Massively Parallel Processors: A Hands-on Approach launches today, authored by Dr. David B. Kirk, NVIDIA Fellow and former chief scientist, and Dr. Wen-mei Hwu, who serves at the University of Illinois at Urbana-Champaign as Chair of Electrical and Computer Engineering in the Coordinated Science Laboratory, co-director of the Universal Parallel Computing Research Center and principal investigator of the CUDA Center of Excellence. The textbook, which is 256 pages, is the first aimed at teaching advanced students and professionals the basic concepts of parallel programming and GPU architectures. Published by Morgan Kaufmann, it explores various techniques for constructing parallel programs and reviews numerous case studies. With conventional CPU-based computing no longer scaling in performance and the world’s computational challenges increasing in complexity, the need for massively parallel processing has never been greater. GPUs have hundreds of cores capable of delivering transformative performance increases across a wide range of computational challenges. The rise of these multi-core architectures has raised the need to teach advanced programmers a new and essential skill: how to program massively parallel processors.

A product can be of low quality for several reasons, such as it was shoddily manufactured, its components were improperly designed, its architecture was poorly conceived, and the product's requirements were poorly understood. Quality must be designed in. You can't test out enough bugs to deliver a high-quality product. The quality assurance (QA) process is vital for the delivery of a satisfactory system. In this last part in this series, we will concentrate on portions of the methodology particularly aimed at improving the quality of the resulting system. The software testing techniques described earlier in this series constitute one component of quality assurance, but the pursuit of quality extends throughout the design flow. For example, settling on the proper requirements and specification cannot be overlooked as an important determinant of quality. If the system is too difficult to design, it will probably be difficult to keep it working properly.