The effect of coefficient quantization optimization on filtering performance and gate count

Abstract. Digital filters are an essential component of Digital Signal Processing (DSP) applications and play a crucial role in removing unwanted signal components from a desired signal. However, digital filters are known to be resource-intensive and consume a large amount of power, making it important to optimize their design in order to minimize hardware requirements such as multipliers, adders, and registers. This trade-off between filter performance and hardware consumption can be influenced by the quantization of filter coefficients. Therefore, this thesis investigates the quantization of Finite Impulse Response (FIR) filter coefficients and analyzes its impact on filter performance and hardware resource consumption. A method called dynamic quantization is introduced and an algorithm for step-by-step dynamic quantization is provided to improve upon the results obtained with the classical fixed point quantization method. To demonstrate the effectiveness of this approach, the dynamic quantization of filter coefficients for a Low-pass Equiripple FIR filter is examined and a comparative study of the magnitude response and hardware consumption of the generated filter using both the classical and dynamic quantization methods is presented. By understanding the trade-offs and benefits of each quantization method, engineers can make informed decisions about the most appropriate approach for their specific application

Digital Filters and Signal Processing

Digital filters, together with signal processing, are being employed in the new technologies and information systems, and are implemented in different areas and applications. Digital filters and signal processing are used with no costs and they can be adapted to different cases with great flexibility and reliability. This book presents advanced developments in digital filters and signal process methods covering different cases studies. They present the main essence of the subject, with the principal approaches to the most recent mathematical models that are being employed worldwide

Design of discrete-time filters for efficient implementation

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 325-333).The cost of implementation of discrete-time filters is often strongly dependent on the number of non-zero filter coefficients or the precision with which the coefficients are represented. This thesis addresses the design of sparse and bit-efficient filters under different constraints on filter performance in the context of frequency response approximation, signal estimation, and signal detection. The results have applications in several areas, including the equalization of communication channels, frequency-selective and frequency-shaping filtering, and minimum-variance distortionless-response beamforming. The design problems considered admit efficient and exact solutions in special cases. For the more difficult general case, two approaches are pursued. The first develops low-complexity algorithms that are shown to yield optimal or near-optimal designs in many instances, but without guarantees. The second focuses on optimal algorithms based on the branch-and-bound procedure. The complexity of branch-and-bound is reduced through the use of bounds that are good approximations to the true optimal cost. Several bounding methods are developed, many involving relaxations of the original problem. The approximation quality of the bounds is characterized and efficient computational methods are discussed. Numerical experiments show that the bounds can result in substantial reductions in computational complexity.by Dennis Wei.Ph.D

Multiplierless multirate FIR filter design and implementation

Ph.DDOCTOR OF PHILOSOPH

Digital Filters

The new technology advances provide that a great number of system signals can be easily measured with a low cost. The main problem is that usually only a fraction of the signal is useful for different purposes, for example maintenance, DVD-recorders, computers, electric/electronic circuits, econometric, optimization, etc. Digital filters are the most versatile, practical and effective methods for extracting the information necessary from the signal. They can be dynamic, so they can be automatically or manually adjusted to the external and internal conditions. Presented in this book are the most advanced digital filters including different case studies and the most relevant literature

Energy-efficient Hardware Accelerator Design for Convolutional Neural Network

Department of Electrical EngineeringConvolutional neural network (CNN) is a class of deep neural networks, which shows a superior performance in handling images. Due to its performance, CNN is widely used to classify an object or detect the position of object from an image. CNN can be implemented on either edge devices or cloud servers. Since the cloud servers have high computational capabilities, CNN on cloud can perform a large number of tasks at once with a high throughput. However, CNN on the cloud requires a long round-trip time. To infer an image picture, data from a sensor should be uploaded to the cloud server, and processed information from CNN is transferred to the user. If an application requires a rapid response in a certain situation, the long round-trip time of cloud is a critical issue. On the other hand, an edge device has a very short latency, even though it has limited computing resources. In addition, since the edge device does not require the transmission of images over network, its performance would not be affected by the bandwidth of network. Because of these features, it is ef???cient to use the cloud for CNN computing in most cases, but the edge device is preferred in some applications. For example, CNN algorithm for autonomous car requires rapid responses. CNN on cloud requires transmission and reception of images through network, and it cannot respond quickly to users. This problem becomes more serious when a high-resolution input image is required. On the other hand, the edge device does not require the data transmission, and it can response very quickly. Edge devices would be also suitable for CNN applications involving privacy or security. However, the edge device has limited energy resource, the energy ef???ciency of the CNN accelerator is a very important issue. Embedded CNN accelerator consists of off-chip memory, host CPU and a hardware accelerator. The hardware accelerator consists of the main controller, global buffer and arrays of processing elements (PE). It also has a separate compression module and activation module. In this dissertation, we propose energy-ef???cient design in three different parts. First, we propose a time-multiplexing PE to increase the energy ef???ciency of multipliers. From the fact the feature maps have small values which are de???ned as non-outliers, we increase the energy ef???ciency for computing non-outliers. For further improving the energy efficiency of PE, approximate computing is also introduced. Method to optimize the trade-off between accuracy and energy is also proposed. Second, we investigate the energy-ef???cient accuracy recovery circuit. For the implementation of CNN on edge, CNN loops are usually tiled. During tiling of CNN loops, accuracy can be degraded. We analyze the accuracy reduction due to tiling and recover accuracy by extending et al. of partial sums with very small energy overhead. Third, we reduce energy consumption for DRAM accessing. CNN requires massive data transmission between on-chip and off-chip memory. The energy consumption of data transmission accounts for a large portion of total energy consumption. We propose a spatial correlation-aware compression algorithm to reduce the transmission of feature maps. In each of these three levels, this dissertation proposes novel optimization and design ???ows which increase the energy ef???ciency of CNN accelerator on edge.clos

High-speed fir filter design and optimization using artificial intelligence techniques

Ph.DDOCTOR OF PHILOSOPH

Argonne National Laboratory Reports

This sixth symposium covers process control processes and issues involved in the conversion of fossil fuels into synthetic fuels