Event Type : Webinar

Stay Ahead of the Curve: European Union Environmental Compliance Update 2024 for Electronics Manufacturers

Ensure your company is up to date with the latest environmental regulations out of the European Union affecting electronics manufacturers in 2024. This essential webinar will cover all the key changes and new developments in EU regulations to help you maintain compliance.

Join regulatory expert Randy Flinders as he provides an in-depth overview of the critical updates to EU environmental regulations, including:

• EU RoHS Exemptions Updates
• EU Persistent Organic Pollutants Regulation Update
• EU REACH Update
• EU Proposed PFAS Ban Update
• Other significant EU Regulations impacting electronics manufacturers

Take advantage of this opportunity to ask your questions during a live Q&A session.

Space is limited, so register now to secure your spot!

Compressive Sensing (CS) has been deployed in a variety of fields including wideband spectrum sensing, active user detection and antenna arrays. In massive MIMO arrays, CS has been applied to reduce the number of measurements required to verify the arrays excitation in a production environment. All follow the general approach of creating the sparsity needed for CS by subtracting the measured far-field or near-field of the test array from that of a ‘gold standard’ array measured under identical conditions. In our initial work the reconstruction of array excitation with a mean square error (MSE) of −30dB was achieved for a 20×28 element array antenna at half wavelength spacing using just 1.5% (177 samples) of the samples needed for a conventional NF measurement (12,100 samples) employing back projection to the aperture. Critical to the performance is the realization that the CS samples need to be confined to the central region of the NF measurement plane which for a conventional NF to FF planar antenna pattern measurement would offer a massive truncation error. This webinar addresses the optimal sampling strategy needed for this NF approach and presents a statistical performance analysis of the reconstruction accuracy.