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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).

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.

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

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.

The marriage of high performance optics with microfluidics could prove the perfect match for making lab-on-a-chip technologies more practical. Microfluidics, the ability to manipulate tiny volumes of liquid, is at the heart of many lab-on-a-chip devices. Such platforms can automatically mix and filter chemicals, making them ideal for disease detection and environmental sensing. The performance of these devices, however, is typically inferior to larger scale laboratory equipment. While lab-on-a-chip systems can deliver and manipulate millions of liquid drops, there is not an equally scalable and efficient way to detect the activity, such as biological reactions, within the drops.