Michael Picciolo

Title: Michael Picciolo: Innovator in Adaptive Signal Processing

Introduction

Michael Picciolo is a notable inventor based in Silver Spring, MD (US). He has made significant contributions to the field of adaptive signal processing, holding 2 patents that showcase his innovative approach to complex signal processing systems.

Latest Patents

One of his latest patents is the "Multistage Median Cascaded Canceller." This adaptive signal processing system employs a Multistage Wiener Filter, which consists of an analysis section and a synthesis section that includes a processor. The processor utilizes an algorithm to generate a data adaptive linear transformation, compute an adaptive weighting of the data, and apply this weighting to a function of a main input signal and an auxiliary input signal to produce an output signal. The system features multiple building blocks arranged in a Gram-Schmidt cascaded canceller-type configuration, which decorrelate input signals to yield a single filtered output signal. Each building block generates an adaptive weight that is applied to create a local output signal. Notably, the effect of non-Gaussian noise contamination on the convergence margin of error (MOE) is minimal, and including desired signal components in weight training data results in little loss of noise cancellation.

Another significant patent is the "Pseudo-Median Cascaded Canceller." This system also utilizes a pseudo-median cascaded canceller to compute a set of complex adaptive weights and generate a filtered output signal. Similar to his previous invention, it includes several building blocks arranged in a Gram-Schmidt cascaded canceller-type configuration for sequentially decorrelating input signals. Each building block has a local main input channel, a local auxiliary input channel, and a local output channel. The complex adaptive weight generated by each building block is the sample median value of the real and imaginary parts of the ratio of local main input weight training data to local auxiliary input weight training data. The system effectively minimizes the impact of non-Gaussian noise contamination on the convergence MOE, ensuring efficient noise cancellation.

Career Highlights

Michael Picciolo works for the United States as represented by the Secretary of the Navy. His role involves developing advanced signal processing technologies that have applications in various fields, including defense and telecommunications.

Collaborations

Some of his notable coworkers include Karl Robert Gerlach and Jay Scott Goldstein, who have collaborated with him on various projects related to adaptive signal