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Ted Marena of Lattice Semiconductor Corp., points out that designers of digital systems are familiar with implementing the 'leftovers' of their digital design by using FPGAs and CPLDs to glue together various processors, memories, and standard function components on their printed circuit board. In addition to these digital functions, FPGAs and CPLDs can also implement common analog functions using an LVDS input, a simple resistor capacitor (RC) circuit and some FPGA or CPLD digital logic elements to create an analog to digital converter (ADC).

With the consumer demand for richer content and its resultant , increasing high data bandwidth continuing to drive communications systems, coding for error control has become extraordinarily important. One way to improve the bit error rate (BER), while maintaining high data reliability, is to use an error correction technique like the Viterbi algorithm. Originally conceived by Andrew Viterbi as an error-correction scheme for noisy digital communication, the Viterbi algorithm provides an efficient method for forward error correction (FEC) that improves channel reliability. Today, it is used in many digital communications systems in applications as diverse as CDMA and GSM digital cellular, dial-up modems, satellite, deep-space communications and 802.11 wireless LANs. It is also commonly used in speech recognition, keyword spotting and computational linguistics.

The ARM Cortex™-M4 processor is the latest embedded processor by ARM specifically developed to address digital signal control markets that demand an efficient, easy-to-use blend of control and signal processing capabilities. The combination of high-efficiency signal processing functionality with the low-power, low cost and ease-of-use benefits of the Cortex-M family of processors is designed to satisfy the emerging category of flexible solutions specifically targeting the motor control, automotive, power management, embedded audio and industrial automation markets. The Cortex-M4 processor features extended single-cycle multiply-accumulate (MAC) instructions, optimized SIMD arithmetic, saturating arithmetic instructions and an optional single precision Floating Point Unit (FPU). These features build upon the innovative technology that characterizes the ARM Cortex-M series processors…

This book is intended for those who work in or provide components for industries that use digital signal processing (DSP). There is a wide variety of industries that utilize this technology. While the engineers who implement applications using DSP must be very familiar with the technology, there are many others who can benefit from a basic knowledge of its' fundamental principals, which is the goal of this book—to provide a basic tutorial on DSP.

25 March 2010—Nowadays, a phone that doesn’t know where it is or where it’s going can’t really call itself ”smart.” To orient themselves properly, smartphones require not just GPS capability but also an electronic compass, an accelerometer, and increasingly, digital gyroscopes. The point of a gyroscope is to sense any change in an object’s axis of rotation. Up until now, gyroscopes measured movement around the three axes with three sensors—one for pitch, one for yaw, and another for roll. At most, two of these sensors would be combined on a single die. The best you could do was, say, match up a 3- by 5- by 1-millimeter yaw sensor with a 4- by 5- by 1-mm sensor that would detect pitch and roll. But on 15 February, STMicroelectronics unveiled  a 4- by 4- by 1-mm gyroscope whose single sensing structure tracks all three angular motions. It’s a triumph of microelectromechanical systems (MEMS) engineering.

In then the past few years we have seen multiprocessing systems become more mainstream, in fact most modern personal computer CPUs now feature symmetric multiprocessing systems (SMP), where multiple instantiations of the same processor share the processing burden of the applications running on the PC. While SMPs are quite common today, we typically have not seen a shift towards multiprocessing in embedded computing. However, a new type of embedded design technique gives engineers the freedom to intelligently distribute processing functions across a digital subsystem. This article will look at an example of the distributed processing technique using Cypress Semiconductor's PSoC 3 and PSoC 5 architectures, which consist of a main CPU (in this case an 8051 or ARM Cortex M3), a DMA engine, and array of Universal Digital Blocks (UDB).

The first part of this white paper explores the basic concepts behind HDMI, the markets it serves and its leadership role in multimedia interfaces. This is followed by a tutorial on the new capabilities of HDMI 1.4 and their role in providing a richer, more straightforward user experience. Next, we'll explore a series of user case scenarios that illustrate how the HEAC feature can simplify cabling requirements between digital home multimedia devices. The last portion of this paper discusses the architectural considerations and technical details involved with incorporating the Ethernet and Sony/Philips Digital Interconnect Format (S/PDIF) standards into the HDMI system-on-chips (SoCs) to support the HEAC feature.

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."

National Instruments has released a vision module for the PXI platform that provides a high-performance parallel processing architecture for hardware-defined timing, control and image pre-processing. The NI 1483 Camera Link adapter module, in combination with an NI FlexRIO field-programmable gate array (FPGA) board, offers a solution for embedding vision and control algorithms directly on FPGAs which are used to process and analyse an image in real time with little to no CPU intervention. The FPGAs can be used to perform operations by pixel, line and region of interest. They can implement many image processing algorithms that are inherently parallel, including fast Fourier transforms (FFTs), thresholding and filtering.

Field programmable gate arrays (FPGAs) present an efficient and inexpensive alternative when it comes to implementing complete embedded systems along with important peripheral functions. The reconfigurable logic circuitry of an FPGA offers tremendous flexibility. A lesser known feature is that the outputs of a digital FPGA also permit various analogue applications.

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.

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.

It is no secret that field-programmable gate arrays (FPGAs) are getting bigger and more complex all the time. The fabrication process creates smaller transistors and makes more dense chips packing more digital processing per nanometer. Engineers love to see advancement because it means they can do more with modern silicon, and many times NI LabVIEW FPGA Module technology helps by abstracting the complexity to a higher level so that engineers can more smoothly take advantage of these improvements.  Unfortunately, there is one issue with FPGAs that continues to be a time sink and only gets worse with denser FPGAs: compilation time.

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.

In addition to voice connectivity, digital cellular wireless networks such as GSM and its enhancement, GSM-EDGE, can now provide increased data speeds up to a (theoretical) limit of 384ﾠKbps. Third generation mobile networks, such as CDMA2000 and WCDMA or UMTS (Universal Mobile Telecommunications Standards) and TD-SCDMA (China only) are currently being deployed worldwide. These systems offer services such as video streaming, Internet browsing and, by using a technique called High Speed Packet Access (HSPA), they can in theory deliver downlink speeds up to 14,4 Mbps.

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).

Rube Goldberg couldn’t have designed a more elegant confluence of convoluted causal relationships.  Start analyzing the perplexing paradox of the FPGA synthesis market and each link of the chain reveals a bizarre force vector that eventually doubles back onto itself into an unlikely equilibrium that miraculously has held stable for a full decade despite disruptive forces of epic proportions. For over a decade now, Synplify has navigated these waters and has continued to survive and thrive through the unlikeliest of conditions.  Now in the hands of EDA giant Synopsys, the Synplify family of FPGA synthesis tools continues to evolve - with a major upgrade this fall.  When you put a digital design into an FPGA, there are two technologies that determine whether your design fits or doesn’t fit, whether it meets your timing constraints or does not, whether the power consumption will be within your limits (or those of the FPGA), or whether it fails completely, leaving your project at the mercy of major mulligans.   Those two technologies are synthesis and place-and-route.