SlideShare a Scribd company logo
1 of 5
Head office: 3nd floor, Krishna Reddy Buildings, OPP: ICICI ATM, Ramalingapuram, Nellore
www.pvrtechnology.com, E-Mail: pvrieeeprojects@gmail.com, Ph: 81432 71457
A High-Performance FIR Filter Architecture for
Fixed and Reconfigurable Applications
Abstract:
Transpose form finite-impulse response (FIR)filters are inherently pipelined and support
multiple constant multiplications (MCM) technique that results in significant saving of
computation. However, transpose form configuration does not directly support the block
processing unlike direct form configuration. In this paper, we explore the possibility of
realization of block FIR filter in transpose form configuration for area-delay efficient realization
of large order FIR filters for both fixed and reconfigurable applications. Based on a detailed
computational analysis of transpose form configuration of FIR filter, we have derived a flow
graph for transpose form block FIR filter with optimized register complexity. A generalizedblock
formulation is presented for transpose form FIR filter. We have derived a general multiplier-
based architecture for the proposed transpose form block filter for reconfigurable applications. A
low-complexity design using the MCM scheme is also presented for the block implementation of
fixed FIR filters. The proposed structure involves significantly less area delay product (ADP)
and less energy per sample (EPS) than the existing block implementation of direct-form structure
for medium or large filter lengths, while for the short-length filters, the block implementation of
direct-form FIR structure has less ADP and less EPS than the proposed structure. Application
specific integrated circuit synthesis result shows that the proposed structure for block size 4 and
filter length 64 involves 42% less ADP and 40% less EPS than the best available FIR filter
structure proposed for reconfigurable applications. For the same filter length and the same block
size, the proposed structure involves 13% less ADP and 12.8% less EPS than that of the existing
direct-form block FIR structure.
Head office: 3nd floor, Krishna Reddy Buildings, OPP: ICICI ATM, Ramalingapuram, Nellore
www.pvrtechnology.com, E-Mail: pvrieeeprojects@gmail.com, Ph: 81432 71457
Existing Method:
FIR filters of largeorder to meet the stringent frequency specifications.Very often these
filters need to support high sampling ratefor high-speed digital communication. Filter
coefficients very often remain constant and known a priori in signal processing applications.
This feature has been utilized to reduce the complexity of realization of multiplications. Several
designs have been suggested by various researchersfor efficient realization of FIR filters (having
fixed coefficients) using distributed arithmetic (DA) and multiple constant multiplication (MCM)
methods. DA-based designs use lookup tables (LUTs) to store precomputed results to reduce the
computational complexity. The MCM method on the other hand reduces the number of additions
required for the realization of multiplications by common subexpression sharing, when a given
input is multiplied with a set of constants. The MCM scheme is more effective, when a common
operand is multiplied with more number of constants.Block-processing method is popularly used
to derive high-throughput hardware structures. It not only provides throughput-scalable design
but also improves the area-delay efficiency. The derivation of block-based FIR structure is
straightforward when direct-form configuration is used, whereas the transpose form
configuration does not directly support block processing. But, to take the computational
advantage of the MCM, FIR filter is required to be realized by transpose form configuration.
Proposed Method:
Head office: 3nd floor, Krishna Reddy Buildings, OPP: ICICI ATM, Ramalingapuram, Nellore
www.pvrtechnology.com, E-Mail: pvrieeeprojects@gmail.com, Ph: 81432 71457
In this paper, we explore the possibility of realization ofblock level Reconfigurable FIR
filter in transpose form configuration in order to take advantage of the MCM schemes and the
inherentpipelining for area-delay efficient realization of large order FIR filters for both fixed and
reconfigurable applications.
Applications:
1. Digital Signal Processing.
2. Speech processing.
3. Loud speaker equalization.
4. Echo cancellation and adaptive noise cancellation.
Advantages:
High through put, Reduced no of additions.
System Configuration:-
In the hardware part a normal computer where Xilinx ISE 14.3 software can be easily
operated is required, i.e., with a minimum system configuration
HARDWARE REQUIREMENT
Head office: 3nd floor, Krishna Reddy Buildings, OPP: ICICI ATM, Ramalingapuram, Nellore
www.pvrtechnology.com, E-Mail: pvrieeeprojects@gmail.com, Ph: 81432 71457
Processor - Pentium –III
Speed - 1.1 GHz
RAM - 1 GB (min)
Hard Disk - 40 GB
Floppy Drive - 1.44 MB
Key Board - Standard Windows Keyboard
Mouse - Two or Three Button Mouse
Monitor - SVGA
SOFTWARE REQUIREMENTS
 Operating System :Windows95/98/2000/XP/Windows7
 Front End : Modelsim 6.3 for Debugging and Xilinx 14.3 for
Synthesis and Hard Ware Implementation
 This software’s where Verilog source code can be used for design
implementation.
Head office: 3nd floor, Krishna Reddy Buildings, OPP: ICICI ATM, Ramalingapuram, Nellore
www.pvrtechnology.com, E-Mail: pvrieeeprojects@gmail.com, Ph: 81432 71457

More Related Content

More from Pvrtechnologies Nellore

Pre encoded multipliers based on non-redundant radix-4 signed-digit encoding
Pre encoded multipliers based on non-redundant radix-4 signed-digit encodingPre encoded multipliers based on non-redundant radix-4 signed-digit encoding
Pre encoded multipliers based on non-redundant radix-4 signed-digit encoding
Pvrtechnologies Nellore
 

More from Pvrtechnologies Nellore (20)

2016 2017 ieee ece embedded- project titles
2016   2017 ieee ece  embedded- project titles2016   2017 ieee ece  embedded- project titles
2016 2017 ieee ece embedded- project titles
 
A High-Speed FPGA Implementation of an RSD-Based ECC Processor
A High-Speed FPGA Implementation of an RSD-Based ECC ProcessorA High-Speed FPGA Implementation of an RSD-Based ECC Processor
A High-Speed FPGA Implementation of an RSD-Based ECC Processor
 
6On Efficient Retiming of Fixed-Point Circuits
6On Efficient Retiming of Fixed-Point Circuits6On Efficient Retiming of Fixed-Point Circuits
6On Efficient Retiming of Fixed-Point Circuits
 
Pre encoded multipliers based on non-redundant radix-4 signed-digit encoding
Pre encoded multipliers based on non-redundant radix-4 signed-digit encodingPre encoded multipliers based on non-redundant radix-4 signed-digit encoding
Pre encoded multipliers based on non-redundant radix-4 signed-digit encoding
 
Quality of-protection-driven data forwarding for intermittently connected wir...
Quality of-protection-driven data forwarding for intermittently connected wir...Quality of-protection-driven data forwarding for intermittently connected wir...
Quality of-protection-driven data forwarding for intermittently connected wir...
 
11.online library management system
11.online library management system11.online library management system
11.online library management system
 
06.e voting system
06.e voting system06.e voting system
06.e voting system
 
New web based projects list
New web based projects listNew web based projects list
New web based projects list
 
Power controlled medium access control
Power controlled medium access controlPower controlled medium access control
Power controlled medium access control
 
IEEE PROJECTS LIST
IEEE PROJECTS LIST IEEE PROJECTS LIST
IEEE PROJECTS LIST
 
Control cloud-data-access-privilege-and-anonymity-with-fully-anonymous-attrib...
Control cloud-data-access-privilege-and-anonymity-with-fully-anonymous-attrib...Control cloud-data-access-privilege-and-anonymity-with-fully-anonymous-attrib...
Control cloud-data-access-privilege-and-anonymity-with-fully-anonymous-attrib...
 
Control cloud data access privilege and anonymity with fully anonymous attrib...
Control cloud data access privilege and anonymity with fully anonymous attrib...Control cloud data access privilege and anonymity with fully anonymous attrib...
Control cloud data access privilege and anonymity with fully anonymous attrib...
 
Cloud keybank privacy and owner authorization
Cloud keybank  privacy and owner authorizationCloud keybank  privacy and owner authorization
Cloud keybank privacy and owner authorization
 
Circuit ciphertext policy attribute-based hybrid encryption with verifiable
Circuit ciphertext policy attribute-based hybrid encryption with verifiableCircuit ciphertext policy attribute-based hybrid encryption with verifiable
Circuit ciphertext policy attribute-based hybrid encryption with verifiable
 
Closeness through-microaggregation-strict-privacy-with-enhanced-utility-prese...
Closeness through-microaggregation-strict-privacy-with-enhanced-utility-prese...Closeness through-microaggregation-strict-privacy-with-enhanced-utility-prese...
Closeness through-microaggregation-strict-privacy-with-enhanced-utility-prese...
 
A secure-anti-collusion-data-sharing-scheme-for-dynamic-groups-in-the-cloud
A secure-anti-collusion-data-sharing-scheme-for-dynamic-groups-in-the-cloudA secure-anti-collusion-data-sharing-scheme-for-dynamic-groups-in-the-cloud
A secure-anti-collusion-data-sharing-scheme-for-dynamic-groups-in-the-cloud
 
A proximity-aware-interest-clustered-p2 p-file-sharing-system-docx
A proximity-aware-interest-clustered-p2 p-file-sharing-system-docxA proximity-aware-interest-clustered-p2 p-file-sharing-system-docx
A proximity-aware-interest-clustered-p2 p-file-sharing-system-docx
 
Agent based interactions and economic
Agent based interactions and economicAgent based interactions and economic
Agent based interactions and economic
 
A computational-dynamic-trust-model-for-user-authorization-docx
A computational-dynamic-trust-model-for-user-authorization-docxA computational-dynamic-trust-model-for-user-authorization-docx
A computational-dynamic-trust-model-for-user-authorization-docx
 
A distortion-resistant-routing-framework-for-video-traffic-in-wireless-multih...
A distortion-resistant-routing-framework-for-video-traffic-in-wireless-multih...A distortion-resistant-routing-framework-for-video-traffic-in-wireless-multih...
A distortion-resistant-routing-framework-for-video-traffic-in-wireless-multih...
 

Recently uploaded

Architecting Cloud Native Applications
Architecting Cloud Native ApplicationsArchitecting Cloud Native Applications
Architecting Cloud Native Applications
WSO2
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Safe Software
 

Recently uploaded (20)

Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
 
Architecting Cloud Native Applications
Architecting Cloud Native ApplicationsArchitecting Cloud Native Applications
Architecting Cloud Native Applications
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
 
Six Myths about Ontologies: The Basics of Formal Ontology
Six Myths about Ontologies: The Basics of Formal OntologySix Myths about Ontologies: The Basics of Formal Ontology
Six Myths about Ontologies: The Basics of Formal Ontology
 
CNIC Information System with Pakdata Cf In Pakistan
CNIC Information System with Pakdata Cf In PakistanCNIC Information System with Pakdata Cf In Pakistan
CNIC Information System with Pakdata Cf In Pakistan
 
Exploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with MilvusExploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with Milvus
 
MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024
 
Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...
Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...
Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...
 
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, AdobeApidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
 
Artificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : UncertaintyArtificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : Uncertainty
 
FWD Group - Insurer Innovation Award 2024
FWD Group - Insurer Innovation Award 2024FWD Group - Insurer Innovation Award 2024
FWD Group - Insurer Innovation Award 2024
 
Understanding the FAA Part 107 License ..
Understanding the FAA Part 107 License ..Understanding the FAA Part 107 License ..
Understanding the FAA Part 107 License ..
 
Mcleodganj Call Girls 🥰 8617370543 Service Offer VIP Hot Model
Mcleodganj Call Girls 🥰 8617370543 Service Offer VIP Hot ModelMcleodganj Call Girls 🥰 8617370543 Service Offer VIP Hot Model
Mcleodganj Call Girls 🥰 8617370543 Service Offer VIP Hot Model
 
Corporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptxCorporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptx
 
Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...
Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...
Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...
 
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
 
DBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor PresentationDBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor Presentation
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
 
Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...
 
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot TakeoffStrategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
 

18.a high performance fir filter architecture for fixed and reconfigurable applications

  • 1. Head office: 3nd floor, Krishna Reddy Buildings, OPP: ICICI ATM, Ramalingapuram, Nellore www.pvrtechnology.com, E-Mail: pvrieeeprojects@gmail.com, Ph: 81432 71457 A High-Performance FIR Filter Architecture for Fixed and Reconfigurable Applications Abstract: Transpose form finite-impulse response (FIR)filters are inherently pipelined and support multiple constant multiplications (MCM) technique that results in significant saving of computation. However, transpose form configuration does not directly support the block processing unlike direct form configuration. In this paper, we explore the possibility of realization of block FIR filter in transpose form configuration for area-delay efficient realization of large order FIR filters for both fixed and reconfigurable applications. Based on a detailed computational analysis of transpose form configuration of FIR filter, we have derived a flow graph for transpose form block FIR filter with optimized register complexity. A generalizedblock formulation is presented for transpose form FIR filter. We have derived a general multiplier- based architecture for the proposed transpose form block filter for reconfigurable applications. A low-complexity design using the MCM scheme is also presented for the block implementation of fixed FIR filters. The proposed structure involves significantly less area delay product (ADP) and less energy per sample (EPS) than the existing block implementation of direct-form structure for medium or large filter lengths, while for the short-length filters, the block implementation of direct-form FIR structure has less ADP and less EPS than the proposed structure. Application specific integrated circuit synthesis result shows that the proposed structure for block size 4 and filter length 64 involves 42% less ADP and 40% less EPS than the best available FIR filter structure proposed for reconfigurable applications. For the same filter length and the same block size, the proposed structure involves 13% less ADP and 12.8% less EPS than that of the existing direct-form block FIR structure.
  • 2. Head office: 3nd floor, Krishna Reddy Buildings, OPP: ICICI ATM, Ramalingapuram, Nellore www.pvrtechnology.com, E-Mail: pvrieeeprojects@gmail.com, Ph: 81432 71457 Existing Method: FIR filters of largeorder to meet the stringent frequency specifications.Very often these filters need to support high sampling ratefor high-speed digital communication. Filter coefficients very often remain constant and known a priori in signal processing applications. This feature has been utilized to reduce the complexity of realization of multiplications. Several designs have been suggested by various researchersfor efficient realization of FIR filters (having fixed coefficients) using distributed arithmetic (DA) and multiple constant multiplication (MCM) methods. DA-based designs use lookup tables (LUTs) to store precomputed results to reduce the computational complexity. The MCM method on the other hand reduces the number of additions required for the realization of multiplications by common subexpression sharing, when a given input is multiplied with a set of constants. The MCM scheme is more effective, when a common operand is multiplied with more number of constants.Block-processing method is popularly used to derive high-throughput hardware structures. It not only provides throughput-scalable design but also improves the area-delay efficiency. The derivation of block-based FIR structure is straightforward when direct-form configuration is used, whereas the transpose form configuration does not directly support block processing. But, to take the computational advantage of the MCM, FIR filter is required to be realized by transpose form configuration. Proposed Method:
  • 3. Head office: 3nd floor, Krishna Reddy Buildings, OPP: ICICI ATM, Ramalingapuram, Nellore www.pvrtechnology.com, E-Mail: pvrieeeprojects@gmail.com, Ph: 81432 71457 In this paper, we explore the possibility of realization ofblock level Reconfigurable FIR filter in transpose form configuration in order to take advantage of the MCM schemes and the inherentpipelining for area-delay efficient realization of large order FIR filters for both fixed and reconfigurable applications. Applications: 1. Digital Signal Processing. 2. Speech processing. 3. Loud speaker equalization. 4. Echo cancellation and adaptive noise cancellation. Advantages: High through put, Reduced no of additions. System Configuration:- In the hardware part a normal computer where Xilinx ISE 14.3 software can be easily operated is required, i.e., with a minimum system configuration HARDWARE REQUIREMENT
  • 4. Head office: 3nd floor, Krishna Reddy Buildings, OPP: ICICI ATM, Ramalingapuram, Nellore www.pvrtechnology.com, E-Mail: pvrieeeprojects@gmail.com, Ph: 81432 71457 Processor - Pentium –III Speed - 1.1 GHz RAM - 1 GB (min) Hard Disk - 40 GB Floppy Drive - 1.44 MB Key Board - Standard Windows Keyboard Mouse - Two or Three Button Mouse Monitor - SVGA SOFTWARE REQUIREMENTS  Operating System :Windows95/98/2000/XP/Windows7  Front End : Modelsim 6.3 for Debugging and Xilinx 14.3 for Synthesis and Hard Ware Implementation  This software’s where Verilog source code can be used for design implementation.
  • 5. Head office: 3nd floor, Krishna Reddy Buildings, OPP: ICICI ATM, Ramalingapuram, Nellore www.pvrtechnology.com, E-Mail: pvrieeeprojects@gmail.com, Ph: 81432 71457