An FPGA Implementation of the LMS Adaptive Filter for Audio Processing

Elhossini, Ahmed; Areibi, Shawki; Dony, R.D.

doi:10.1109/reconf.2006.307767

Cited by 40 publications

(11 citation statements)

References 3 publications

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“…In order to be effectively removed, the ambient noise must be highly correlated with the noise components in the speech signal. The Least Mean Square (LMS) adaptive filter is used for implementing the noise cancellation because of its simplicity and suitability for real-time applications [14] [15].The block diagram of Adaptive Noise Canceller is shown in figure 2. In figure 2,The error at the output of the filter can be expressed as, e n =d n -W n T u n (1) which is simply the desired output minus the actual filter output.…”

Section: Iiadaptive Noise Cancellermentioning

confidence: 99%

Implementation of adaptive noise canceller using FPGA for real-time applications

Thilagam¹,

Karthigaikumar

2015

2015 2nd International Conference on Electronics and Communication Systems (ICECS)

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This paper presents the architecture and implementation of a real time adaptive NLMS filter for non-stationary noise cancellation in a real-time environment.The active noise control techniques using adaptive digital filters are very much suitable and well proven.The proposed efficient Adaptive Noise Canceller is realized using Xilinx System Generator 12.3 on Spartan 3E FPGA. System Generator is a DSP design tool from Xilinx that enables the use of The Mathworks model-based design environment ,Simulink for FPGA design.All FPGA implementation steps including Synthesis, place and Route are automatically performed to generate an FPGA programming file and the design is evaluated in terms of speed, hardware resources and power dissipation. Keywords-LMS Adaptive filter, Noise canceller, Xilinx system generator 12.3, Spartan 3E, VHDL I.

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Section: Iiadaptive Noise Cancellermentioning

confidence: 99%

Implementation of adaptive noise canceller using FPGA for real-time applications

Thilagam¹,

Karthigaikumar

2015

2015 2nd International Conference on Electronics and Communication Systems (ICECS)

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“…Audio processing requires less bandwidth than video processing, audio application can benefit from specialization, a sound synthesizer implemented using PAM system [18] producing real time audio of 256 different voices at up to 44.1 kHz. In [19] three different architectures for implementing a least mean square (LMS) adaptive filtering algorithm, using a 16 bit fixed-point arithmetic representation is shown. These architectures are implemented using the Xilinx multimedia board as an audio processing system.…”

Section: Dsp System Using Fpgamentioning

confidence: 99%

An Overview of Reconfigurable Hardware for Efficient Implementation of DSP Algorithms

Kadam¹

2014

IOSRJEN

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-Reconfigurable hardware is emerging as the best option for the efficient implementation of complex and computationally expensive signal processing algorithms. Reconfigurable hardware exploits the benefit of high of computational efficiency of hardware as well as flexibility of software implementation. Field Programmable Gate Array (FPGA) which finds wide range of applications in the field of signal processing, wireless communication, image and video processing has gained popularity as a reconfigurable logic over past decade. In this paper, various hardware aspects of reconfigurable such as architectures and models including external coupling and run-time reconfigurable systems have been studied. Moreover, a case study of most widely used commercial FPGA technologies from Xilinx and upcoming three dimensional 3D-FPGA architecture is presented. It is revealed that the reconfigurable hardware can be used in a variety of DSP applications. FPGA implementation of digital signal processing applications show enhanced outcome in terms of speed as compared to software implementation and previously reported architecture.

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“…There are usually two ways to implement the LMS algorithm, hardware implementation and software implementation [8], [9]. The hardware implementation of the algorithm in an FPGA has good real-time ability, but requires large resources.…”

Section: Fig2flowchart Of the Lms Algorithmmentioning

confidence: 99%

FPGA Implementation of an Adaptive Noise Canceller

Lan¹,

Zhang²

2008

2008 International Symposiums on Information Processing

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This paper proposes an FPGA implementation of anAdaptive Noise Canceller using the Least Mean Square (LMS) algorithm. The hardware architecture is synthesized using the Xilinx Spartan-3e Starter Kit as the target board. The experimental result of the hardware implementation shows the performance of LMS algorithm under different conditions and the feasibility of our architecture. A comparison between hardware and pure software implementation is then made with different filter taps.

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An FPGA Implementation of the LMS Adaptive Filter for Audio Processing

Cited by 40 publications

References 3 publications

Implementation of adaptive noise canceller using FPGA for real-time applications

Implementation of adaptive noise canceller using FPGA for real-time applications

An Overview of Reconfigurable Hardware for Efficient Implementation of DSP Algorithms

FPGA Implementation of an Adaptive Noise Canceller

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