To this end, a cooperative design-separate encoding approach was suggested for a decentralized hypothesis testing system[4, 5] where a distributional distance was used as a criterion for quantizer design in order to yield a manageable design procedure.
EDQ shows good localization performance so as to be used as an efficient initialization for quantizer design [14, 26].
The EDQ design is verified through simulations in[15, 17], showing that EDQ can be used as an efficient initialization for quantizer design because of its good localization performance.
Since they do not utilize any statistics about the sensor readings for quantizer design, there will be no reduction in redundancy by the quantization scheme.
We show that using the distance as a new cost function provides several benefits for quantizer design in distributed estimation: first, minimizing the probabilistic distance results in quantizers that generate the codewords maximizing the logarithmic quantized posterior distribution (log p(theta |hat {mathbf {z}}_{1}^{M})) on the average, thus improving the estimation accuracy.
The challenge here is that since the Lloyd algorithm was devised for quantizer design when a local metric (e.g., reconstruction error of local sensor readings) is used as a cost function, simply replacing it by a global metric may cause problems.
To avoid the encoding complexity, a suboptimal approach (i.e., linear estimator) was considered for quantizer design [5].
For a distributed detection system, the authors in[6] proposed a heuristic procedure for quantizer design that minimizes the upper bound of the probability of error.
FLSQ shows robust performance in the mismatch situations where the parameters used in quantizer design are different from those characterizing the simulation conditions.
More importantly, the bit-allocations and quantizer-step sizes found in [5] can be used for practical design of WZ-transform codes as long as high-rate approximations hold.
