It has been announced that MathWorks has introduced Release 2019a of MATLAB and Simulink. The release contains new products and important enhancements for artificial intelligence (AI), signal processing, and static analysis, along with new capabilities and bug fixes across all product families.

Jos Martin, Senior Engineering Manager at MathWorks, investigates the likely Artificial Intelligence (AI) 2019 trends for scientists and engineers

The new 5G standards have arrived and the corresponding networks are predicted to roll-out across the UK in late 2019. However, what can we expect in the lead-up to ubiquitous 5G? Ken Karnofsky, Senior Strategist for Signal Processing Applications at MathWorks, plays future gazer and gives us his market predictions for 2019.

Autonomous systems conjure up a future filled with self-driving cars, humanoid robots, and buzzing drones bearing packages from Amazon. The underlying technology continues to mature at a rapid pace, and in doing so is pulling designers in hundreds of new directions. In fact, the sheer number and variety of design options raises an interesting question: what does 'autonomy' actually mean to us? By Jim Tung, MathWorks Fellow

In today's Autumn Statement the Chancellor of the Exchequer Philip Hammond, is expected to unveil new infrastructure projects worth billions of pounds. A new report, Skills: Meeting Demand, says this presents the UK with the opportunity to build engineering talent base for the future via innovative and creative recruitment. It’s a sentiment likely to be echoed by many in the tech and engineering sectors.

Science, technology, engineering and maths (STEM) sectors are struggling to attract school leavers and the industries are seeking solutions to their ongoing skill gaps. During research by MathWorks, STEM professionals were asked whether students are being targeted too late to develop a love of STEM subjects? The response was affirmative; half of respondents believe students need to be encouraged towards these sectors much younger than is conventi...

With pressure from modern broadband wireless standards such as LTE to minimise out-of-band emissions and to maintain power efficiency, it is more important than ever to ensure effective linear amplification from power amplifiers (PAs). Digital pre-distortion (DPD) is a fundamental building block used in wireless communication systems today for better efficiency. By reducing the distortion created by running power amplifiers in their non-linear re...

MathWorks today announced that Simulink code generation targets have been built into Freescale’s new Motor Control Development Toolbox through Embedded Coder. The toolbox, consisting of Simulink motor control blocks and target-ready code generation support, lets automotive and industrial controls engineers design motor control systems using Freescale microprocessors in IEC 61508 (SIL3) and ISO 26262 (ASIL-D) compliant systems.

An automated process to generate C code from MATLAB algorithms is designed to help engineering teams more quickly and efficiently from algorithm development to production-ready code. By Arvind Ananthan

From time to time, marshalling events occur in stable markets placing difficult new requirements on established system designs. Subsequently, innovative new design tools and processes emerge to address shortcomings in the legacy design flows for the established systems. In the case of wireless systems, the emergence of coexistence represents one of these marshalling events. In particular, the connectivity boom in consumer electronics and the impo...

MathWorks today announced new capabilities within Embedded Coder as part of advancing Simulink production code generation capabilities for embedded systems. Engineers in the automotive, industrial automation and machinery industries can now generate production optimized code involving several key industry standards and technologies.

MathWorks announced that Thien eDrives (formerly ATB Technologies) used MATLAB and Simulink to model, simulate, and implement an electric motor control system on TI’s C2000 microcontroller unit (MCU). By applying Model-Based Design, Thien eDrives moved rapidly from the first prototype to the final series, reducing development time by 50%.

MathWorks has introduced Simulink Code Inspector, which facilitates the review of source code generated from Simulink models. Aerospace engineers can now use Simulink Code Inspector to create detailed model-to-code and code-to-model inspection reports that help satisfy source code verification and traceability objectives specified in DO-178B Table A-5.

MathWorks invites you to join leading engineers in aerospace and automotive industries to exchange ideas, share applications and learn how MATLAB® and Simulink® are being used to deliver the highest levels of design assurance.

MathWorks announced that Simulink Design Verifier now includes Polyspace analysis technology for automated error detection in Simulink models. Simulink Design Verifier 2.0 integrates Polyspace error detection with existing property proving and test generation capabilities to help reduce the time required to find and fix the root cause of design errors, decreasing the overall cost of verification and validation.

MathWorks has announced that Simulink Design Verifier now includes Polyspace analysis technology for automated error detection in Simulink models. Simulink Design Verifier 2.0 integrates Polyspace error detection with existing property proving and test generation capabilities to help reduce the time required to find and fix the root cause of design errors, decreasing the overall cost of verification and validation.

MathWorks today announced the availability of MATLAB Coder, which enables design engineers to automatically generate readable, portable C and C++ code directly from their MATLAB algorithms. This new product eliminates the need to manually translate MATLAB algorithm code into C and C++ code for prototyping, implementation, and software integration. This automation results in a faster, more efficient system-development workflow.

MathWorks announced that Mitsuba, manufacturer of wiper motors, used MATLAB and Simulink to develop the controller of the innovative reversing wiper and deliver a complete system in 81% less time than estimated. By adopting Model-Based Design, including automatic production code generation, Mitsuba reduced their project development time from 16 weeks to 3 weeks.