Alireza Shoa

Run-Time Reconfigurable Systems for Digital Signal Processing Applications: A Survey

Today’s digital signal processing (DSP) applications use computationally complex and/or adaptive algorithms and have stringent requirements in terms of speed, size, cost, power consumption, and throughput. Efficient hardware implementation techniques should be employed to meet the requirements of these applications. Run-Time Reconfiguration (RTR) is a promising technique for reducing the hardware required for implementing DSP systems as well as improving the performance, speed and power consumption of these systems. In this survey, we explain different issues in run-time reconfigurable systems and list the implemented systems which support run-time reconfiguration. We also describe different applications of run-time reconfiguration and discuss the improvements achieved by applying run-time reconfiguration.

Optimized Atom Position and Coefficient Coding for Matching Pursuit-Based Image Compression

In this paper, we propose a new encoding algorithm for matching pursuit image coding. We show that coding performance is improved when correlations between atom positions and atom coefficients are both used in encoding. We find the optimum tradeoff between efficient atom position coding and efficient atom coefficient coding and optimize the encoder parameters. Our proposed algorithm outperforms the existing coding algorithms designed for matching pursuit image coding. Additionally, we show that our algorithm results in better rate distortion performance than JPEG 2000 at low bit rates.

Tree structure search for matching pursuit

Matching pursuit has found many applications recently especially in very low bit rate video coding. In this paper we show how the complexity of matching pursuit can be reduced from O(N) to O(log(2N)) using tree structured dictionaries. Moreover, we show how tree structured dictionaries provide an efficient coding strategy that is more resilient to error than random coding. Our simulation results showed an improvement of about 3 dB in PSNR can be achieved using the code provided by the tree structured dictionary.

Adaptive Rate-Distortion Optimal In-Loop Quantization for Matching Pursuit

In this paper, an adaptive in-loop quantization technique is proposed for quantizing inner product coefficients in matching pursuit. For each matching pursuit (MP) stage a different quantizer is used based on the probability distribution of MP coefficients. The quantizers are optimized for a given rate budget constraint. Additionally, our proposed adaptive quantization scheme finds the optimal quantizers for each stage based on the already encoded inner product coefficients. Experimental results show that our proposed adaptive quantization scheme outperforms existing quantization methods used in matching pursuit image coding.

A block based encoding algorithm for matching pursuit image coding

A new encoding algorithm is proposed for encoding matching pursuit parameters in image compression applications. The new algorithm is a block based coding approach that takes advantage of correlations in atom positions and inner product coefficients in a rate distortion optimal manner. Simulation results show the proposed algorithm significantly improves the performance of the existing encoding algorithms and outperforms JPEG2000 at low bit rates.

Progressive Coding of a Gaussian Source Using Matching Pursuit

In this paper, the application of matching pursuit (MP) in progressive coding of memoryless Gaussian sources is studied. In addition, a detailed analysis of the rate-distortion performance of our proposed MP encoder is presented, and the distortion of the MP encoder is derived in terms of dictionary size and number of quantization levels and the optimum parameters are calculated. Our analysis is based on a probabilistic model for matching pursuit residual vectors. Our simulation results verify the accuracy of our analysis and show that matching pursuit can produce an embedded bitstream with comparable quality to existing quantizers. The MP encoder outperforms quantizers that are capable of producing embedded bitstreams.

Adaptive Quantization for Matching Pursuit

We propose an adaptive quantization scheme for matching pursuit. Different quantizers are used in different matching pursuit (MP) stages based on the probability distribution of MP coefficients. The quantizers are optimized for a given rate budget constraint. Additionally, our proposed adaptive quantization scheme finds the optimal quantizers for each stage based on the information known to both encoder and decoder. Our quantization scheme outperforms existing MP encoders

Power savings in channel equalizers using run-time reconfiguration

A channel equalizer is a major component in every communication system. Adaptive channel equalizers, which are used to compensate varying channels, are one of the most computationally intensive and power consuming components of a receiver. Power consumption is a major issue in portable communication systems and methods that provide power savings for channel equalizers are essential in mobile communications. Run-time reconfiguration (RTR) is a promising approach for reducing power consumption of many applications. We use run-time reconfiguration to reduce the power consumption of adaptive channel equalizers. Moreover, a simpler method (bypassing) is presented to take advantage of run-time reconfiguration benefits while avoiding the complexity and overhead of designing a run-time reconfigurable system. Simulation results show that the proposed run-time reconfigurable architecture reduces the power consumption by 15%.

Variable Length Coding for Fixed Rate, Low Latency, Low Complexity Compression Applications

In order to maximize coding efficiency the coding algorithm must ensure the probability of encoding a sequence of n quantized symbols at a rate smaller than R is maximized (i.e. there is no need to increase the quantization step size). This optimization problem is different from the one solved by algorithms like Huffman coding in which it is assumed that a large sequence of symbols are being coded. We proposed a new coding algorithm that solves the above optimization problem.

Optimization of Matching Pursuit Encoder Based on Analytical Approximation of Matching Pursuit Distortion

Distortion of matching pursuit is calculated in terms of matching pursuit encoder parameters for uniformly distributed signals and dictionaries. Then, the MP encoder is optimized using the analytically derived approximation for MP distortion. Our simulation results show that this optimized MP encoder exhibits optimum performance for nonuniform signal and dictionary distributions as well