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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).

bowl and pairing off to come up with a way to create and commercialise sensors and switches that generate their own power. The idea is that the parts will make external power sources redundant - because they can convert energy from body heat, light and vibrations straight into electricity. Self powered electronics have already sporadically been used in technology like wall-mount remote control units for air conditioners, says Nikkei, but existing parts are bulky and cost a couple thousand yen a piece. 3,000 yen is about $35 - which means they're not the best bet, financially, yet.

In many instances, the way embedded software is structured and how it interacts with the hardware in a system can have a profound effect on the transient immunity performance of a system. It can be impractical and costly to completely eliminate transients at the hardware level, so the system and software designers should plan for the occasional erroneous signal or power glitch that could cause the software to perform erratically. Erratic actions on the part of the software can be classified into two different categories:

Earlier in this series, we touched on one problem that can arise when sampling an analog signal, namely the problem of aliasing. There are three other issues with signal sampling to which we now turn our attention: digitization effects, finite register length effects, and oversampling. So far, weve assumed that all of the signals were measuring are continuous analog values; i.e., our measurements are completely accurate. Even in the cases in which we have noise, the underlying assumption is that the measurement itself, for example the noisy sensor output voltage, is known precisely.

We’re all familiar with the general idea of a filter: it removes something that we don’t want from something we do want. Coffee filters that pass the liquid coffee but retain the grounds or air filters that pass clean air but trap the dust and other pollutants are two common examples of mechanical filters in everyday life. That same concept can be applied to noisy electrical signals to pass through the “true” signal of interest while blocking the undesirable noise signal. Looking at Figure 2.5c below, imagine for a moment that the signal of interest is in the lower-frequency region and that the noise signal is in the higher-frequency region. Ideally, we’d like to be able to get rid of that high-frequency noise, leaving just the signal component that we want.

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.

In traditional short-haul microwave transmission (that is, line-of-sight microwave transmissions operating in the 18 GHz and 23 GHz radio bands),RF design engineers typically are concerned with signal aspects such as fade margins, signal reflections, multipath signals, and so forth. Like an accountant seeking to balance a financial spreadsheet, an RF design engineer normally creates an RF budget table, expressed in decibels (dB), in order to establish a wireless design. Aspects like transmit power and antenna gain are registered in the assets (or plus) column, and free space attenuation, antenna alignment, and atmospheric losses are noted in the liabilities (or minus) column. The goal is to achieve a positive net signal strength adequate to support the wireless path(s) called for in the design.

The center piece of our toolset is the software integrated development environment or IDE. MPLAB IDE has enjoyed many years of evolution cracking Microchip’s popular catalogue of micro controllers and digital signal controllers. This presentation will cover these topics. Look at MPLAB and its components. An MPLAB IDE overview, MPLAB’s hardware components including starter kits and demonstration and evaluation kits and finally we attempt to answer the question why use Microchip tools.

A shielded transformer is a two-winding transformer, usually delta"star connected and serves the following purposes: Voltage transformation from the distribution voltage to the equipment's utilization voltage. Converting a 3-wire input power to a 4-wire output thereby deriving a separate stable neutral for the power supply wiring going to sensitive equipment. Keeping third and its multiple harmonics away from sensitive equipment by allowing their free circulation in the delta winding. Softening of high-frequency noise from the input side by the natural inductance

While the topic of timing has already been raised in previous parts in this series, the discussion here will be expanded to include the execution and response time of the software functions. When discussing timing in embedded software, there are typically two types of timing requirements, rate of execution and response time. Rate of execution deals with the event-to-event timing within a software function. It can be the timing between changes in an output, time between samples of an input, or some combination of both.

Imagine that a guest is about to depart from your house. She (or he) pauses to check her appearance in an antique-looking mirror mounted near the front door. Suddenly, the image of your guest undergoes a Matrix-like 'ripple' and is replaced with a strange face saying… …actually, we'll move on to consider what the face might say in a moment, but first let me introduce you to a few underlying concepts. Just a few days ago as I pen these words, I came across about a very cool website that describes a really cunning idea called a Magic Mirror (http://diymagicmirror.com).

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.

March has seen two significant announcements from FPGA start-ups with innovative architectures: Tabula, with their time-domain-multiplexed architecture, and TierLogic, implementing their routing switches in a layer of thin-film transistors. Both approaches promise to significantly reduce the die size and cost of high-end FPGAs. But before these announcements broke, a relatively unnoticed paper at February's International Symposium on FPGAs described what may be the most radical technology of them all: FPGAs using electromechanical relays. No, this is not an early April Fool's joke, nor is it one of those "let's see if anyone will publish this one" academic exercises. The paper presented work by professors and students at the Stanford University departments of electrical engineering and computer science, and researchers at Altera Corp. The work was supported in part by DARPA funding.