Skip to main content
SpringerLink
Log in

Flexible Adaptive FIR Filter Designs Using LMS Algorithm

  • Conference paper
  • First Online:
VLSI Design and Test (VDAT 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1066))

Included in the following conference series:

Abstract

This paper proposes the least mean square (LMS) algorithm based versatile, vector, and fault tolerant adaptive finite impulse response (FIR) filter designs. Here, the M-taps versatile design is to perform the filter operation with the number of filter co-efficients varied from 2 to M. The M-taps vector design is to perform \(\lfloor \frac{M}{L}\rfloor \) numbers of L-taps filter operations in parallel, where \(M\ge L\). The fault tolerant M-taps filter is to perform the \((M-N)\)-taps fault free filter operation under the N numbers of faulty filter kernels, where \((M-N)\ge 2\). All the existing and proposed designs are implemented with 45 nm CMOS technology. The proposed 16-taps vector adaptive filter design achieves \(93\%\) of improvement in throughput as compared with the distributed arithmetic based design.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 89.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 119.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Schuldt, C., Lindstrom, F., Li, H., Claesson, I.: Adaptive filter length selection for acoustic echo cancellation. Sig. Process. 89(6), 1185–1194 (2009)

    Article  Google Scholar 

  2. Gu, Y., Tang, K., Cui, H., Wen, D.: Convergence analysis of a deficient-length LMS filter and optimal-length sequence to model exponential decay impulse response. IEEE Signal Process. Lett. 10(1), 4–7 (2003)

    Article  Google Scholar 

  3. Gu, Y., Tang, K., Cui, H.: LMS algorithm with gradient descent filter length. IEEE Signal Process. Lett. 11(3), 305–307 (2004)

    Article  Google Scholar 

  4. Gong, Y., Cowan, C.F.N.: A novel variable tap-length algorithm for linear adaptive filters. In: IEEE International Conference on Acoustics, Speech, and Signal Processing, pp. ii–825 (2004)

    Google Scholar 

  5. Gerlach, L., Paya-Vaya, G., Blume, H.: An area efficient real- and complex-valued multiply-accumulate SIMD unit for digital signal processors. In: IEEE Workshop on Signal Processing Systems (SiPS), pp. 1–6 (2015)

    Google Scholar 

  6. Robelly, J.P., Cichon, G., Seidel, H., Fettweis, G.: Implementation of recursive digital filters into vector SIMD DSP architectures. In: IEEE International Conference on Acoustics, Speech, and Signal Processing, pp. 1–4 (2004)

    Google Scholar 

  7. Jenkins, W.K., Schnaufer, B.A.: Fault tolerant adaptive filters based on the block LMS algorithm. In: IEEE International Symposium on Circuits and Systems, pp. 862–865 (1993)

    Google Scholar 

  8. Lee, C.-Y., Meher, P.K.: Fault tolerant dual basis multiplier over \(GF(2^m)\). In: IEEE Circuits and Systems International Conference on Testing and Diagnosis, pp. 1–4 (2009)

    Google Scholar 

  9. Basiri M, M.A., Sk, N.M.: An efficient hardware based higher radix floating point MAC design. ACM Trans. Des. Autom. Electron. Syst. (TODAES) 20(1), 15:1–15:25 (2014)

    Google Scholar 

  10. Mandal, A., Mishra, R., Kaushik, B.K., Rizvi, N.Z.: Design of LMS adaptive radar detector for non-homogeneous interferences. IETE Tech. Rev. 33(3), 269–279 (2015)

    Article  Google Scholar 

  11. Ting, L.-K., Woods, R., Cowan, C.F.N.: Virtex FPGA implementation of a pipelined adaptive LMS predictor for electronic support measures receivers. IEEE Trans. Very Large Scale Integr. (VLSI) Syst. 13(1), 86–95 (2005)

    Google Scholar 

  12. Santha, K.R., Vaidehi, V.: Design of efficient architectures for 1-D and 2-D DLMS adaptive filters. Integr. VLSI J. 40(3), 209–225 (2007)

    Article  Google Scholar 

  13. Kim, H., Soeleman, H., Roy, K.: Ultra-low power DLMS adaptive filter for hearing aid applications. IEEE Trans. Very Large Scale Integr. (VLSI) Syst. 11(6), 1058–1067 (2003)

    Article  Google Scholar 

  14. Meher, P.K., Park, S.Y.: Area-delay-power efficient fixed-point LMS adaptive filter with low adaptation-delay. IEEE Trans. Very Large Scale Integr. (VLSI) Syst. 22(2), 362–371 (2014)

    Article  Google Scholar 

  15. Rocher, R., Herve, N., Menard, D., Sentieys, O.: Fixed-point configurable hardware components for adaptive filters. IEURASIP J. Embed. Syst. 1–13 (2006). https://link.springer.com/article/10.1155/ES/2006/23197

  16. Goel, P., Chandra, M.: VLSI implementations of retimed high speed adaptive filter structures for speech enhancement. Microsyst. Technol. 24(12), 4799–4806 (2018)

    Article  Google Scholar 

  17. Khan, M.T., Ahamed, S.R.: A new high performance VLSI architecture for LMS adaptive filter using distributed arithmetic. In: IEEE Computer Society Annual Symposium on VLSI (ISVLSI), pp. 219–224 (2017)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Electronics and Communication Engineering, IIITDM, Kurnool, 518007, India

    M. Mohamed Asan Basiri

Authors
  1. M. Mohamed Asan Basiri
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to M. Mohamed Asan Basiri .

Editor information

Editors and Affiliations

  1. Computer Science and Engineering, Indian Institute of Technology Indore, Indore, India

    Anirban Sengupta

  2. Department of Electronics and Communication Engineering, Indian Institute of Technology Roorkee, Roorkee, India

    Sudeb Dasgupta

  3. Department of Electrical Engineering, Indian Institute of Technology Bombay, Mumbai, India

    Virendra Singh

  4. Department of Electrical Engineering, Indian Institute of Technology Ropar, Rupnagar, India

    Rohit Sharma

  5. Electrical Engineering, Indian Institute of Technology Indore, Indore, India

    Santosh Kumar Vishvakarma

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Mohamed Asan Basiri, M. (2019). Flexible Adaptive FIR Filter Designs Using LMS Algorithm. In: Sengupta, A., Dasgupta, S., Singh, V., Sharma, R., Kumar Vishvakarma, S. (eds) VLSI Design and Test. VDAT 2019. Communications in Computer and Information Science, vol 1066. Springer, Singapore. https://doi.org/10.1007/978-981-32-9767-8_6

Download citation

  • DOI: https://doi.org/10.1007/978-981-32-9767-8_6

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-32-9766-1

  • Online ISBN: 978-981-32-9767-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation