Bilinear Algorithms and VLSI Implementations of Forward and Inverse MDCT with Applications to MP3 Audio


Lehigh University has developed bilinear algorithms to compute forward and inverse modified discrete cosine transforms (MDCT/IMDCT) for a complete solution to MP3 audio processing.


By using this technology, the multiplication operation along the critical path is minimized, allowing for 20%-30% faster computing than existing solutions. This is because sub-groups can be computed in parallel and there is only one multiplication along the critical path. In software applications, the bilinear algorithm has small code size and hence less memory requirement. In hardware applications, the structures bilinear circuit is faster and smaller.


Industry sectors for this technology include consumer electronics, broadcasting and internet media, music/ movie industry, and equipment manufacturers.


Lehigh ID #: 010408-03



MP3 audio processing computations previously required code specific to the frame size. The algorithm used here is able to solve the problem by unifying the MDCT computations, thereby yielding a smaller code which requires less memory.


• Efficient bilinear algorithms for MDCT and IMDCT of both short and long block sizes

• Improved critical path delay of VLSI architecture for MDCT and IMDCT of both short and long block sizes (20% to 30% faster circuit)

• Type-(1x) unified algorithm and architecture for MP3 audio (forward/inverse and short/long), capable of processing 1 long block or 1 short block per cycle

• With pipelined architecture, the number of outputs can be reduced by 1/3, further improving the silicon footprint



Digital signal processing technologies has become very advanced in the past decade. This is because this kind of technology is stable, reliable and offers enhanced performance and programmability. Applications are continually expanding and end users are increasing demand for better and faster solutions. The market size for software products within the consumer electronics niche is estimated to be around $2.3 billion, each year creating more opportunity for advanced products to enter the market.



Lehigh University is currently looking to out-license this technology:

App Type Country Serial No. Patent No. File Date Issued Date Expire Date
Utility United States 12/865,831 8/2/2010   10/16/2013
For Information, Contact:
Alan Snyder
VP, Research & Grad Programs
Lehigh University
Xingdong Dai
Meghanad Wagh
Portable Devices