Glossary
Key Terms
Active Noise Cancellation (ANC) is a technology designed to reduce or neutralize unwanted ambient sounds by generating sound waves of opposite phase. Often associated with audio headphones, ANC appears in various industries—from automotive and aviation to household appliances. Its main benefit is creating a quieter environment, allowing users to focus on what they want to hear, such as music, podcasts, or in-flight announcements.
Adaptive Body Bias (ABB) is a power management technique used in integrated circuits to control and optimize the electrical characteristics of transistors. By modifying the voltage applied to the body (or substrate) of a transistor, ABB helps fine-tune performance, reduce power consumption, and manage leakage currents, particularly in advanced semiconductor processes.
An Analog-to-Digital Converter (ADC) is an electronic component or circuit that transforms analog signals (continuous and varying over time, such as sound waves, temperature readings, or sensor outputs) into digital data that computers and microcontrollers can process. ADCs play a pivotal role in bridging the analog and digital worlds, enabling advanced data analysis, signal processing, and system control.
Always-On Keyword Spotting is a voice recognition technique designed to continuously listen for a specific “wake word” or “trigger phrase” (e.g., “Hey Siri,” “Ok Google,” “Alexa”) without consuming large amounts of power or computational resources. It allows devices to remain in a low-power or idle state until they detect the designated keyword, at which point they activate more advanced voice processing or related functionalities.
Always-On Solutions refer to systems, services, or devices that remain consistently operational or continuously accessible, ensuring minimal downtime and uninterrupted performance. This can apply to cloud-based infrastructures, server deployments, network services, and more. The goal is to provide high availability, seamless user experiences, and dependable real-time functionality for mission-critical tasks and applications.
An AMBA-based Chassis refers to a system-on-chip (SoC) design framework built around the Advanced Microcontroller Bus Architecture (AMBA) specifications. ARM originally introduced AMBA to standardize the on-chip communication and interfaces among various IP blocks (intellectual property blocks), such as processors, memory controllers, peripherals, and accelerators. By using an AMBA-based chassis, chip designers can streamline system integration, enhance reusability, and ensure compatibility across different components and vendors.
Analog design in the context of integrated circuit (IC) design is a discipline that focuses on the creation of circuits that operate in and are optimized for continuous time-domain behavior.Typical objectives of analog design include:
A signal processing circuit that interfaces with analog sensors to condition, amplify, filter, and convert signals into a digital format suitable for further processing. AFEs typically include amplifiers, filters, analog-to-digital converters (ADCs), and noise reduction circuits.
A technology that superimposes digital information—graphics, text, sound—onto a user’s physical view of the real world in real time. By combining sensory data and context-aware computing, AR enriches human experiences, from gaming and navigation to industrial design and collaborative work.
Automotive MCU: A dedicated microcontroller that integrates processing cores, memory, peripherals, and communication interfaces specifically validated for automotive environments. It must comply with automotive-grade certifications such as AEC-Q100 (Automotive Electronics Council) and adhere to safety standards like ISO 26262 for functional safety.
A device or algorithm that compresses audio signals into a smaller, more manageable format (encoding) and then restores them (decoding) for playback. This process can be lossy (discarding some data to reduce size) or lossless (maintaining exact fidelity).
A circuit or algorithm that continuously adjusts the sampling frequency of incoming audio data to match a different output sampling frequency, compensating for clock drift or mismatch between source and destination devices.
A dynamic power management technique that modulates the supply voltage of a semiconductor device based on real-time performance and workload requirements. AVS leverages closed-loop feedback from performance monitors such as process, voltage, and temperature (PVT) sensors to optimize power efficiency while ensuring stable operation.
A signal processing circuit that interfaces with analog sensors to condition, amplify, filter, and convert signals into a digital format suitable for further processing. AFEs typically include amplifiers, filters, analog-to-digital converters (ADCs), and noise reduction circuits.
Battery management system (BMS) is technology dedicated to the oversight of a battery pack, which is an assembly of battery cells, electrically organized in a row x column matrix configuration to enable delivery of targeted range of voltage and current for a duration of time against expected load scenarios.
A method for focusing or steering electromagnetic or acoustic signals in a chosen direction by combining inputs or outputs from multiple elements in an antenna or sensor array. The term can also apply to multichannel microphone arrays for picking up or filtering out sounds from particular directions.
BLE is a Low-power wireless communication, short-range connectivity. It is used mainly for IoT devices, smart home automation, fitness trackers. BLE is defined by the Bluetooth SIG and operates under the IEEE 802.15.1 standard. Optimized for minimal energy consumption in wireless applications.
It is mathematically defined by the following formula:
BT is a High-bandwidth audio streaming, reliable connection. It s used for Wireless headphones, automotive infotainment. Defined by the Bluetooth SIG, it follows IEEE 802.15.1. Enables robust, low-latency connections for audio and voice applications.
A branch of AI that focuses on developing techniques for automatic extraction, analysis, and comprehension of useful information from digital images, videos, or other visual inputs, replicating human-like visual perception.
A power-saving technique in digital circuits that selectively disables the clock signal to idle logic blocks, preventing unnecessary switching activity and dynamic power consumption. Implemented using AND gates, latch-based enable signals, or automated synthesis tools.
An essential step in digital IC design that constructs and optimizes the clock distribution network to minimize clock skew and ensure synchronized signal propagation across the chip. CTS involves inserting clock buffers, balancing clock latencies, and considering power and area constraints.
A field that applies digital signal processing (DSP) and machine learning techniques to enhance audio quality, extract features, and process sound in real-time. It involves noise suppression, beamforming, speech enhancement, and AI-driven sound classification.
Cortex-M: A set of ARM processor cores optimized for microcontroller and embedded contexts, focusing on low power, deterministic real-time performance, and a simplified architecture. Variants include Cortex-M0, M0+, M3, M4, M7, M23, and M33, each balancing different performance and power requirements.
A digital logic tool or framework that auto-generates control logic (e.g., state machines, bus controllers) for embedded or SoC designs, based on configuration parameters.
A central processing unit is a semiconductor chip that interprets and carries out the basic instructions and operations required by computer programs. It fetches, decodes, and executes instructions, relying on internal registers and arithmetic logic units (ALUs) to handle calculations and data flow.
A device that converts digital signals (bits) into analog voltages or currents, enabling audio playback or analog control from digital data.
A power converter that steps up or steps down DC voltage levels (e.g., from a battery) to meet the regulated input requirements of various subsystems.
A mechanism enabling peripherals (e.g., network cards, disk controllers) or coprocessors to read from or write to system memory independently, thus freeing the CPU to perform other tasks while the transfer completes.
A neural network with multiple layers—often including convolutional, recurrent, or fully connected layers—designed to automatically learn hierarchical representations of data. By stacking many layers, DNNs can model complex, non-linear relationships and patterns.
A specialized microprocessor designed for high-speed mathematical operations required in digital signal processing applications. It features parallel processing units, specialized instructions for multiply-accumulate (MAC) operations, and optimized memory architectures.
A decentralized method of data processing in which computation resources (servers, micro data centers, or specialized devices) operate at the network’s edge—closer to endpoints rather than relying solely on centralized cloud infrastructures.
Embedded Vision integrates image capture and processing directly into devices with limited computational resources, allowing them to analyze visual data locally instead of relying on external servers. This enables real-time insights and reduces bandwidth usage.
Embedded systems are specialized computer systems—often with minimal resources—designed to perform a dedicated function or set of functions within a larger mechanical or electrical system. They are typically optimized for size, power, and reliability, and can be found in everything from industrial machinery and automobiles to consumer electronics and medical devices.
Energy harvesting is the process of capturing and converting small amounts of ambient or environmental energy (e.g., solar, thermal, vibration, radio frequency) into usable electrical power. It allows low-power electronic devices or sensor nodes to operate with minimal or no battery reliance, particularly in remote or hard-to-reach locations.
Optimized neural network architectures that reduce computational complexity, memory footprint, and power consumption while maintaining high inference accuracy. Techniques include quantization, pruning, and sparsity-based optimizations.
A computing paradigm where data processing occurs directly at the device level (on the edge), minimizing reliance on centralized cloud servers. It leverages AI acceleration, local processing units, and real-time inference models.
FinFET (Fin Field-Effect Transistor) is a type of 3D transistor where the channel is formed on a thin “fin” protruding from the substrate. This design improves gate control over the channel and reduces leakage current, enabling higher performance and lower power consumption compared to traditional planar transistors.
FD-SOI (Fully Depleted Silicon-on-Insulator) is a semiconductor technology where an ultra-thin silicon layer rests atop a buried oxide layer. By fully depleting the transistor channel of charge carriers, FD-SOI improves electrostatic control, reduces leakage currents, and enables low-power, high-performance designs compared to conventional bulk silicon processes.
GNSS (Global Navigation Satellite System) is an umbrella term for satellite-based positioning, navigation, and timing (PNT) systems (e.g., GPS, GLONASS, Galileo, BeiDou). By receiving signals from multiple satellites, GNSS-enabled devices can triangulate their precise location, velocity, and time reference anywhere on Earth.
A clock domain crossing (CDC) technique that ensures seamless clock signal transitions without generating spurious pulses that could cause functional errors. Implemented using mux-based clock selection and safe state transitions.
Hi-Fi (High Fidelity) refers to high-quality audio reproduction that closely matches the original recording in terms of clarity, range, and minimal distortion. Hi-Fi systems strive for accurate and transparent sound, allowing listeners to hear music or other audio content as intended by the creators.
High Performance Computing (HPC) refers to the use of parallel processing techniques, powerful hardware (clusters, supercomputers, GPU arrays), and specialized software to rapidly process large, complex datasets or perform computationally intensive tasks. HPC systems enable breakthroughs in scientific research, data analytics, engineering simulations, and beyond.
Home appliances are electrical or mechanical devices used in households to perform a wide range of routine tasks—such as cooking, cleaning, food preservation, and climate control. Examples include refrigerators, washing machines, microwave ovens, and air conditioners.
Home automation involves using smart devices and control systems to automate everyday household functions—like lighting, climate control, security, and entertainment—often via networked and remote-access technologies.
A headset is a head-worn device combining headphones (for audio output) and often a microphone (for input), allowing hands-free communication and immersive audio experiences in environments such as gaming, voice calls, or multimedia playback.
Hearables are smart, in-ear devices (often wireless) that go beyond simple audio playback to offer advanced functionalities such as fitness tracking, voice assistance, and real-time translation. Also known as “smart earbuds,” hearables integrate microphones, sensors, and Bluetooth connectivity in a compact form factor.
A dedicated hardware device designed to generate, manage, and store cryptographic keys securely. HSMs provide tamper-resistant protection and accelerate encryption, decryption, and authentication operations.
A network of connected devices (sensors, appliances, vehicles) that collect, exchange, and act on data over the internet or local networks, often with minimal human intervention.
The process of conceptualizing, schematic drafting, layout, and fabrication of integrated circuits (chips) that power electronic devices, from microcontrollers to complex SoCs.
The process of conceptualizing, schematic drafting, layout, and fabrication of integrated circuits (chips) that power electronic devices, from microcontrollers to complex SoCs.
A technique in speech processing that continuously listens for specific “wake words” (e.g., “Hey Siri”), activating voice assistants only upon detection.
A Low Dropout linear regulator that provides a stable DC output at a voltage only slightly lower than its input, useful where low noise or small voltage differences are required.
An advanced deep learning model trained on vast amounts of text data to understand and generate human-like language. Uses transformer architectures and massive-scale datasets.
A process in digital design where high-level hardware description language (HDL) code is translated into optimized gate-level netlists. It involves logic minimization, timing optimization, and power-aware transformations.
A clock generation circuit that minimizes phase noise and timing jitter by synchronizing an output frequency with a stable reference clock. Used in high-speed data transmission and precision timing circuits.
A specialized hardware unit designed to accelerate machine learning computations by optimizing matrix multiplications and data movement. MLAs feature tensor cores, low-precision arithmetic, and on-chip memory for efficient AI inference.
A branch of AI focused on developing algorithms that enable computers to learn from and make predictions based on data patterns. Uses models such as neural networks, decision trees, and regression analysis.
A technique that integrates both analog and digital signal processing in a single system, enabling seamless conversion between the two domains. Common in sensor interfacing, audio, and RF communication.